HBN_WG Nelson for Frontiers of Personalized Medicine A Fresh Look Ahea

Movement Toward Personalized Medicine and Individualized Health for Cancer: 

Movement Toward Personalized Medicine and Individualized Health for Cancer William G. Nelson, M.D., Ph.D. Director, Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins

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United States (U.S.) Cancer Mortality for 2010* * Jemal A et al. CA Cancer J Clin CA 60: 277-300 (2010) Men 21% decrease for men and 12% for women in death rates for all cancers since 1990 Women

Impact of Cancer in the U.S.* : 

Impact of Cancer in the U.S.* About 44% of men and 38% of women will develop cancer in their lifetimes 1,529,560 new cancer cases in 2010 569,490 cancer deaths in 2010 84% of all cases are diagnosed after age 60 31% of all cases are diagnosed after age 80 American Cancer Society, Cancer Facts & Figures 2004 and 1997 , citing NIH data *American Cancer Society, Cancer Facts & Figures 2004 and 1997; Jemal A et al. CA Cancer J Clin 60: 277-300 (2010)

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treat disease when symptoms arise and normal function is compromised morphological understanding of disease state high financial and disability costs intervene before symptoms appear and preserve normal function cellular/molecular understanding of evolving disease process opportunity for improved efficacy and efficiency 20 th century medicine 21 st century medicine prevention of disease and preservation of health at a population scale prediction of disease risk permitting less toxic and more effective intervention personalization of risks and treatments; greater participation of patients in health care decision-making implications Transformation of Medicine by Translational Research * *adapted from Hood L et al. (2005-6)

Mapping/Sequencing of the Human Genome: 

Mapping/Sequencing of the Human Genome Science, Feb 16, 2001 New technologies for molecular profiling of cancer cells Unprecendented opportunities for the discovery and development of new approaches to cancer treatment and prevention Greatly augmented public expectations Increased cancer care costs? Milestone in molecular biology Revolutionized cancer genetics and epidemiology

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11 colorectal cancers 11 breast cancers 24 pancreas cancers 22 gliomas 22 meduloblastomas 2 leukemias 1 breast cancer 1 breast cancer 4 granulosa cell tumors 1 lung cancer Sanger 1 melanoma *Vogelstein B AACR Annual Meeting (2010) Washington University British Columbia Cancer Research Centre Sanger Institute Science, Feb 16, 2001 Whole Exome Sequences of 100 Human Cancers* 3142 mutated genes 286 tumor suppressors 33 oncogenes SKCCC

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High Dimensional Sequencing of Cancer Genomes Reveals Both Common and Rare Gene Defects in Human Cancers * *Wood LD et al. Science 318: 1108-13 (2007) PI3KCA PI3KCA TP53 TP53

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Hypermethylation (versus normal tissues) Hypomethylation (versus normal tissues) Genome-Wide Epigenetic Alterations in Metastases from Men Dying of Prostate Cancer* * Yegnasubramian S, Aryee MJ et al. (2011)

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*Brock MV et al. New Engl J Med 358: 1118-28 (2008) stage 1 non-small cell lung cancer (no spread to mediastinal lymph nodes) DNA methylation marker negative DNA methylation marker positive DNA methylation marker negative DNA methylation marker positive DNA Methylation Biomarkers Improve Lung Cancer Staging*

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* Hegi ME et al. New Engl J Med 352: 997-1003 (2005) MGMT CpG Island/Promoter Methylation and Glioblastoma Response to Temozolomide *

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Kaplan-Meier Survival Analysis: Estimates Difference in Hazard Rates “Waterfall” Plots: Show Heterogeneity in Benefit Evaluation of Treatment Benefit: Second-Line Hormonal Therapy for Prostate Cancer* *Scher HI et al. Lancet, 375: 1437-46 (2010); De Bono JS et al. New Engl J Med, 364: 1995-2005 (2011)

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pretreatment biopsies from subjects (n = 30) with melanoma treated with an anti-PD-1 antibody Heterogeneous Responses of Melanoma to Anti-PD-1* *Brahmer JR et al. J Clin Oncol 28: 3167-75 (2010)

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Knocked-In Mutation in PI3KCA Compound #1 Growth Inhibition (IC 50 ) Compound #7 Growth Inhibition (IC 50 ) E545K 100 nM 1000 nM H1047R 1200 nM 170 nM wild-type 970 nM 1800 nM Mutation-Selective PIK3CA Inhibitors in Breast Cancer* PIK3CA mutations seen in breast cancers (25% or more in metastatic disease) *Ben Ho Park laboratory collaboration with Plexxikon Human breast cell growth inhibitory activity of PIK3CA-targeted drugs

Trends in DNA sequencing… Impact of New Technologies*: 

*Hutchison CA Nucl Acids Res 35: 6227-37 (2007) *Service RF Science 311: 1544-6 (2006) Trends in DNA sequencing… Impact of New Technologies * 2007: $10 -4 /bp 2008: $10 -5 /bp 2009: $10 -6 /bp … and still going …

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*Srivastava S et al. Clin Cancer Res 14: 5672-7 (2008) NCI Translational Research Working Group Pathways to Development*

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Biomarker Discoveries Biomarker Assay Platforms Regulatory/Systems Considerations Integration into Clinical Practice Test Marker Specimen Company Disease Indication PCA3 RNA urine Dianon prostate cancer predicts prostate biopsy outcome MGMT methylation DNA tissue MDxHealth glioblastoma predicts response to temozolomide GSTP1 methylation DNA urine tissue LabCorp MDxHealth prostate cancer predicts prostate biopsy outcome AMACR protein tissue many prostate cancer diagnosis aid DNA Beaming, PARE, MSP, nanoMSP , MOB, COMPARE, GEMINI germline DNA variants somatic DNA mutations, translocations, etc. somatic DNA somatic methylation changes RNA expression changes, splice variants protein expression changes CLIA, biospecimen collection/ archiving, HIPAA, health record information technology Translational Development of Molecular Biomarkers at SKCCC: What are the Challenges?

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Biomarker Discoveries Biomarker Assay Platforms Regulatory/Systems Considerations Integration into Clinical Practice Test Marker Specimen Company Disease Indication PCA3 RNA urine Dianon prostate cancer predicts prostate biopsy outcome MGMT methylation DNA tissue MDxHealth glioblastoma predicts response to temozolomide GSTP1 methylation DNA urine tissue LabCorp MDxHealth prostate cancer predicts prostate biopsy outcome AMACR protein tissue many prostate cancer diagnosis aid DNA Beaming, PARE, MSP, nanoMSP , MOB, COMPARE, GEMINI germline DNA variants somatic DNA mutations, translocations, etc. somatic DNA somatic methylation changes RNA expression changes, splice variants protein expression changes CLIA, biospecimen collection/ archiving, HIPAA, health record information technology Translational Development of Molecular Biomarkers at SKCCC: What are the Challenges?

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The 5-me CpG-Binding Domain (MBD2) Protein MBD2 Selectively Interacts with DNA Containing Symmetrically Methylated CpG Dinucleotides * 5-me CpG dinucleotide binding pocket * Kielkopf C et al. (2011); Whys N et al. (2011); Yegnasubramanian S et al. Nucl Acids Res, 34: e19 (2006) MBD2 binding to 5-me CpG-DNA fluorescence polarization: EC 50 = 222 +/- 67 nM isothermal calorimetry : K D = 88 +/- 62 nM ΔH = 10.2 +/- 0.6 kcal/M

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whole genome tiled arrays high density SNP arrays high dimensional DNA sequencing Captured Methylated DNA can be Analyzed Using Many Different Platforms* *Yegnasubramanian S et al. (2011)

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COMPARE-MS Analyses of CpG Island Methylation * A B C *Yegnasubramanian S et al. Nucl Acids Res, 34: e19 (2006) prostate cancers normal prostate (organ donors) non-cancerous prostate in glands with cancers

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GSTP1 / APC / RAR b methylation serum PSA DNA methyl v PSA PSA DNA methyl *Baden J et al. J Urol 182: 1186-93 (2009) Urine DNA Methylation Biomarkers Outperform Serum PSA Testing in Prediction of “Positive” Prostate Cancer Biopsy* for GSTP1 / APC / RAR b methylation : PPV = 100% NPV = 79%

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Detection of Cancer-Specific Mutations in Blood and Body Fluids: Opportunity for Screening and Early Detection* *Diehl F et al. Gastroenterology 135: 489-98 (2008) colon cancer stage % mutant DNA in stool “ BEAMing ” for mutant DNA Unmet medical needs: poor colonoscopy quality timing of repeat colonoscopy (for US: 32% repeat colonoscopies within 5 years of a negative procedure)

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Improving Cancer Health at a Population Scale: Covered Lives in the Johns Hopkins Health System Organization (Characteristics) Population Size Johns Hopkins Community Physicians (Primary Care Provider Network) >260,000 Johns Hopkins Priority Partners (Medicaid Health Maintenance Organization) >185,000 Johns Hopkins Employee Health Program (Health Insurance Plan) >50,000 Johns Hopkins US Family Health Plan (Provider to US Government and Military Employees and Families) Enrolling SKCCC Cancer Prevention and Control Program already working with these entities to establish cancer screening guidelines and improve screening performance - first project focuses on reducing over-screening for prostate cancer among elderly men

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Individualized Health/Personalized Medicine at SKCCC and at Johns Hopkins Medicine What are the Challenges/Opportunities? Individualized Health Initiative (IHI) Planning led by Provost, Dean of Engineering, and SKCCC Director Envisioned $1.5B project (>$0.5B investment in Epic health record/management system- investment in research information technology needed ) Brings together Schools of Medicine, Public Health, Engineering, Nursing, Arts & Sciences, Business, Applied Physics Laboratory $30M Malone gift to Engineering $30M Commonwealth Foundation gift to SKCCC for Personalized Cancer Medicine Information for Health Learning Communities for Health Laboratory for Advanced Biotechnologies for Health Organizational Model for Affordable Health Design and Deploy New Research Information System Develop Bioethics Framework Design New Approach for Clinical Trials Build Network Throughout Johns Hopkins Health System Develop Better Measurements, Diagnostics, and Treatments Epigenome / Genome Core High Performance Computing Core Statistics Core Biorepository Apply IHI Principles, Methods, and Tools to Population Health at Significantly Lower Cost IHI Director’s Office Applied Physics Laboratory Johns Hopkins University Johns Hopkins Medicine

Current Challenges of Drug Discovery and Development Flow of Approved Products*: 

Current Challenges of Drug Discovery and Development Flow of Approved Products* Lead Identification Chemistry Lead Optimization Pharmacologic Candidate Selection Production & Formulation Safety Assessment Phase I Clinical Trials Phase II Clinical Trials Phase III Clinical Trials approval by U.S. Food and Drug Administration *adapted from Barker A, National Cancer Institute; PhRMA (www.phrma.org)

Current Challenges of Drug Discovery and Development Flow of Approved Products*: 

Current Challenges of Drug Discovery and Development Flow of Approved Products* Phase I Clinical Trials Phase II Clinical Trials Phase III Clinical Trials approval by U.S. Food and Drug Administration <1% 861 drugs in clinical trials for cancer in 2009 (122 for lung ca, 107 for breast ca, 70 for colorectal ca, 103 for prostate ca) 1-2 new drugs approved for cancer each year (of a yearly total of 20 or more for all uses) development costs >$1B/drug development time >10 years *adapted from Barker A, National Cancer Institute; PhRMA (www.phrma.org)

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Phase 1 (Toxicity) Testing Goal is to determine the dose and dose-schedule for the drug (MTD = maximally tolerated dose; DLT = dose-limiting toxicity) Phase 3 (Comparative Efficacy) Goal is to test patient benefit Phase 2 (Efficacy) Testing Goal is to estimate/define drug benefit (Response rates: complete responses + partial responses) Investigational New Drug (IND) application filed with Food and Drug Administration Historical Development Pathway for Anti-Cancer Drugs FDA Approval/Labeling for Marketing

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Phase 1/2 (Toxicity/Efficacy) Testing Goals are: ( i ) to determine optimal biological dose (the dose that maximizes “on-target” effects while minimizing “off-target” effects, using molecular biomarker of pharmacodynamic action ), and (ii) to estimate drug benefit in setting with maximal chance of efficacy ( using molecular biomarker of risk/for indication ) Phase 3 (Comparative Efficacy) Goal is to test patient benefit Investigational New Drug (IND) application filed with Food and Drug Administration New Development Pathway for Anti-Cancer Drugs FDA Approval/Labeling for Marketing

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target/pathway discovery target “credentialing” drug discovery (identification of leads; iterative process of synthesis/analysis) preclinical drug development (safety/toxicity; manufacturing) Investigational New Drug (IND) application filed with Food and Drug Administration The Discovery and Development of Anti-Cancer Drugs: Role of “Translational Research”* * Schilsky RL et al. Clin Cancer Res. 14: 5685-91 (2008)

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target/pathway discovery target “credentialing” drug discovery (identification of leads; iterative process of synthesis/analysis) preclinical drug development (safety/toxicity; manufacturing) Investigational New Drug (IND) application filed with Food and Drug Administration The Discovery and Development of Anti-Cancer Drugs: Role of “Translational Research”* * Schilsky RL et al. Clin Cancer Res. 14: 5685-91 (2008) coordinated development of molecular biomarkers as “companion diagnostics’

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Advances in genome analysis technologies are driving advances in personalized cancer care Major unmet medical need for diagnostic products deployed at a population scale- evolving health system structure may drive value of individualized health Need for increased predictability of anti-cancer drug/treatment development creating appetite for risk stratification tools ( personalized medicine ) Final Thoughts