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Define Treatment Success in the Age of Pharmacogenomics

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Define Treatment Success in the Age of Pharmacogenomics ,June 2016 - Barcelona -14 13 Spain Define treatment success in the age of pharmacogenomics IMPROVING THE PATIENT’S LIFE THROUGH MEDICAL EDUCATION www.excemed.org Outline MS response Future Biomarkers Pharmacogenomics biomarkers directions Outline MS response Future Biomarkers Pharmacogenomics biomarkers directions Introduction Definition*: Biomarker • “ A characteristic that is objectively measured and evaluated as an indicator of normal biological processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention” *Biomarkers Definitions Working Group. Clin Pharmacol Ther 2001;69: 89-95 Introduction MS is quite a heterogeneous disease…strong need for biomarkers that capture heterogeneity and may help in: 1. MS diagnosis and disease stratification 2. Prediction of disease course 3. Identification of new therapies beneficial for the disease 4. Personalized therapy based on the prediction of treatment response and identification of patients at high risk for side effects Introduction Biomarkers in MS: 1. Molecular biomarkers 2. Imaging biomarkers Introduction Molecular biomarkers in MS Category Description Predictive biomarkers Measured in neurologically asymptomatic individuals to identify those at risk of developing MS (first-degree relatives of MS patients) Molecular biomarkers Diagnostic biomarkers Can we discriminate patients who have MS from patients with other neurological conditions, autoimmune conditions, or healthy individuals? (patients with symptoms suggestive of MS / CIS / RIS) Disease activity biomarkers Measured in patients with relapsing-remitting and progressive disease courses and aid in the distinction between MS patients with benign and aggressive disease courses Treatment response Measured in patients receiving MS therapies in order to biomarkers identify those individuals who are at risk for treatment failure and/or serious adverse drug reactions Comabella M, Montalban X. Lancet Neurol 2014;13:113 Introduction Molecular biomarkers in MS Category Description Predictive biomarkers Measured in neurologically asymptomatic individuals to identify those at risk of developing MS (first-degree relatives of MS patients) Molecular biomarkers Diagnostic biomarkers Can we discriminate patients who have MS from patients with other neurological conditions, autoimmune conditions, or healthy individuals? (patients with symptoms suggestive of MS / CIS / RIS) Disease activity biomarkers Measured in patients with relapsing-remitting and progressive disease courses and aid in the distinction between MS patients with benign and aggressive disease courses Treatment response Measured in patients receiving MS therapies in order to biomarkers identify those individuals who are at risk for treatment failure and/or serious adverse drug reactions Comabella M, Montalban X. Lancet Neurol 2014;13:113 Outline MS response Future Biomarkers Pharmacogenomics biomarkers directions Pharmacogenomics How to identify markers associated with response to treatment in MS? Pharmacogenomics How to identify markers associated with response to treatment in MS? Pharmacogenomics: “Application of genome technologies such as gene expression profiling, single nucleotide polymorphisms (SNP) screens, high-throughput DNA/RNA sequencing to predict patient response and toxicity to drugs” Pharmacogenomics How to identify markers associated with response to treatment in MS? Pharmacogenomics: “Application of genome technologies such as gene expression profiling, single nucleotide polymorphisms (SNP) screens, high-throughput DNA/RNA sequencing to predict patient response and toxicity to drugs” Ultimate goal... “To facilitate individualization of patient treatment...” DMT Interferon-beta Glatiramer acetate Mitoxantrone Natalizumab Oral therapies Fingolimod Laquinimod Teriflunomide BG12 Monoclonal antibodies Alemtuzumab Daclizumab Rituximab Ocrelizumab Ofatumumab DMT Interferon-beta Glatiramer acetate Mitoxantrone Natalizumab Individualized therapy Oral Potential risk for treatment failure therapies Tx. A Tx. B Tx. C Fingolimod Laquinimod Teriflunomide BG12 Adverse “Administration of treatment reactions to those patients who are most likely to respond to it” Monoclonal antibodies Alemtuzumab Daclizumab Rituximab Ocrelizumab Ofatumumab Pharmacogenomics in MS: The future A Clinical and radiological C Others characteristics Proteomics Metabolomics Variables .............. A B C D A1........An B1........Bn C1........Cn D1........Dn 1 % R to treament 1 ……………………………. % R to treament N 2 % R to treament 1 ……………………………. Prediction of response Patients % R to treament N N % R to treament 1 ……………………………. B Transcriptomics % R to treament N D Genetic polymorphisms SNP a SNP d Genes SNP f Non- responder Responder Outline MS response Future Biomarkers Pharmacogenomics biomarkers directions Interferon-beta Genetic studies 1. Candidate gene studies (genes investigated) Category Genes HLA genes HLA class I, HLA class II Complement regulatory proteins CD46 Cytokines IL10, IFNG, CCR5, TGFB1, IL-1b, IL-4, RANTES, IP9, TNFA, TNFB, IL1B, IL12RB2, IL10RB, IL7RA, TNF, PTGS2, CD274, CTLA4 IFN receptor and signalling IFNAR1, IFNAR2, IRF5, IRF8, USP18, ISG12, ISG56, ISG20, IFP53, pathway SP100, IRF4, IRF9, TYK2, PIAS1, SOCS3, IFNB1 Interferon induced anti-viral MX1, TLR7, IDO1, GBP1, PRKR response molecules Pro-apoptotic molecules TRAIL, TRAILR-1, TRAILR-2, TRAILR-3, TRAILR-4, CASP10, CASP3, CASP2, CASP7, CASP5, CASP8, TSC22, CFLAR, DUSP1 Validated IFN-a response markers IL28B Others VCAM, ICAM1, ITGB2, ITGA4, DRD3, DBH, Th, SPRR2A, PRM3, SYN2, LEP, P21, PRKCA Interferon-beta Genetic studies 1. Candidate gene studies (significant associations) Reference Genes or gene rs numbers Observation combinations associated Cunningham et al. IFNAR1 GTn repeat in promoter Associated with response (2005) CTSS rs1136774 PSMB8 rs2071543 MX1 rs2071430, rs17000900 Wergeland et al. IL10 rs1800896 Trend toward fewer MRI (2005) rs1800871 lesions in non-GCC rs1800872 haplotypes st Martínez et al. (2006) IFNG CAn repeat in 1 intron Associated with response O’Doherty et al. JAK2 rs1887429 Associated with response (2009) IL10RB rs2834167 Combination 1 GBP1 rs12089335 PIAS1 rs10162905 JAK2 rs1887429 Combination 2 IL10 rs1800872 CASP3 rs2019978 Interferon-beta Genetic studies 1. Candidate gene studies (significant associations) Reference Genes or gene rs numbers Observation combinations associated Cénit et al. (2009) GPC5 rs10492503 Associated with response Alvarez-Lafuente et CD46 rs2724385 Associated with response al. (2011) Vosslamber et al. IRF5 rs2004640 Associated with response (2011) rs4728142 Kulakova et al. (2012) CCR5 (32 bp deletion) rs333 Associated with response TGFB1 rs1800469 López-Gómez et al. TNFRSF10A (TRAILR-1) rs20576 Associated with response (2013) Malhotra et al. (2013) USP18 rs2542109 Associated with response Bustamante et al. PELI3 rs2277302 Associated with response (2015) GABRR3 rs832032 Interferon-beta Genetic studies 1. Candidate gene studies Negative results Weak and unreplicated associations Interferon-beta Genetic studies 2. Whole genome SNP screens (4 studies) 1 2 Interferon-beta Genetic studies 2. Whole genome SNP screens Vandenbroeck, Urcelay, Comabella. Pharmacogenomics 2010;11:1137 Interferon-beta Results – intragenic SNPs SNP Chr Gene symbol Gene name Byun et al. (2008) rs4466137 5 HAPLN1 hyaluronan and proteoglycan link protein 1 rs10492503 13 GPC5 Glypican 5 rs9301789 rs794143 4 COL25A1 collagen, type XXV, alpha 1 rs10510779 3 ERC2 ELKS/RAB6-interacting/CAST family member 2 rs6944054 7 LOC442331 similar to dynein, cytoplasmic, light peptide rs4855469 3 FAM19A1 family with sequence similarity 19 (chemokine (C-C motif)-like), member A1 rs4128599 14 NPAS3 neuronal PAS domain protein 3 Comabella et al. (2009) rs12557782 X GRIA3 Glutamate receptor, ionotrophic, AMPA 3 rs7308076 12 CIT Citron (rho-interacting, serine/threonine kinase 21) rs2229857 1 ADAR Adenosine deaminase, RNA-specific rs733254 8 ZFAT Zinc finger and AT hook domain containing rs9527281 13 STARD13 StAR-related lipid transfer (START) domain containing 13 rs11787532 8 ZFHX4 Zinc finger homeobox 4 rs2248202 21 IFNAR2 Interferon (alpha, beta and omega) receptor 2 Interferon-beta Results – intragenic SNPs SNP Chr Gene symbol Gene name Byun et al. (2008) rs4466137 5 HAPLN1 hyaluronan and proteoglycan link protein 1 rs10492503 13 GPC5 Glypican 5 rs9301789 rs794143 4 COL25A1 collagen, type XXV, alpha 1 expressionexpresión en in rs10510779 3 ERC2 ELKS/RAB6tejidobrain-interacting/CASTcerebral tissue family member 2 rs6944054 7 LOC442331 similar to dynein, cytoplasmic, light peptide rs4855469 3 FAM19A1 family with sequence similarity 19 (chemokine (C-C motif)-like), member A1 rs4128599 14 NPAS3 neuronal PAS domain protein 3 Comabella et al. (2009) rs12557782 X GRIA3 Glutamate receptor, ionotrophic, AMPA 3 rs7308076 12 CIT Citron (rho-interacting, serine/threonine kinase 21) rs2229857 1 ADAR Adenosine deaminase, RNA-specific rs733254 8 ZFAT Zinc finger and AT hook domain containing rs9527281 13 STARD13 StAR-related lipid transfer (START) domain containing 13 rs11787532 8 ZFHX4 Zinc finger homeobox 4 rs2248202 21 IFNAR2 Interferon (alpha, beta and omega) receptor 2 Interferon-beta Results – intragenic SNPs SNP Chr Gene symbol Gene name Byun et al. (2008) rs4466137 5 HAPLN1 hyaluronan and proteoglycan link protein 1 rs10492503 13 GPC5 Glypican 5 rs9301789 rs794143 4 COL25A1 collagen, type XXV, alpha 1 rs10510779 3 ERC2 ELKS/RAB6-interacting/CAST family member 2 vía celulartype I IFNde los IFNs rs6944054
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