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Clinical Sequencing Workshop
Clinical Sequencing Workshop - May 29th, 2012
Moderator: Gary Schroth, Senior Director, Expression Application R&D, Illumina
12:00 Registration
12:55 Welcome & Opening Remarks
1:00 Emerging Next-Generation Sequencing Technologies and its Clinical Applications
Thomas Scholl, Vice President, Research & Development, Integrated Genetics / LabCorp
Next-generation sequencing is undergoing accelerating translation into the clinical realm. Several clinical diagnostic tests are available that employ next-generation sequencing and many companies/laboratories have announced launch dates and development plans for additional tests. Some of these products afford improvements on existing themes by harnessing the capacity of next-generation sequencers to increase clinical sensitivity by analyzing disease loci more comprehensively than previously possible. Other products exploit unique characteristics of next-generation sequencing methods to enable entirely new diagnostic assays. An overview of these product categories focusing upon product profiles and technical underpinnings will be presented.
1:30 The Implementation of Next-Generation Sequencing in a CLIA Laboratory - Issues and Challenges
Matthew Ferber, Assistant Professor of Laboratory Medicine & Pathology, Mayo Clinic
Recently there has been much discussion regarding how “massively parallel” or “Next Generation” DNA sequencing (NGS) will impact clinical care. While the technology promises to reduce the cost of sequencing an entire human genome to less than $1,000, one must question the diagnostic utility of complete genome sequencing for routine clinical testing, given the many interpretive challenges posed by this approach. In this presentation we will discuss the promise and pitfalls associated with the clinical application of NGS.
2:00 Afternoon Break
2:30 Translation of Next-Gen Sequencing from Research Applications to a Standardized Lab Developed Test in a CLIA Environment
Andrew Grupe, Senior Director, Pharmacogenomics, Celera
Next generation sequencing (NGS) has transformed the research sequencing landscape. These technologies have enabled a plethora of new discoveries by allowing us to answer questions more cost-effectively than in past and ask questions that were impossible to address by capillary electrophoresis sequencing or high density chip platforms. Translating NGS applications from a research environment to a standardized test offering in a clinical reference laboratory presents multiple challenges. These range from identifying NGS tests that provide clinical value beyond existing tests on traditional platforms, increased needs for a bioinformatics infrastructure to interpret and report results, genome sequence versioning and subscription access to permit revisiting a prior sequence because of the identification of new indications, to consequences of updates to the technology hardware and software as well as reagents of the rapidly changing NGS field. Changes in the regulatory landscape that may impact the use of these technologies are also being contemplated. This presentation will offer a users perspective of these issues.
3:00 Measuring and Ensuring Quality in NGS
Tina Hambuch, Scientific Liaison, Clinical and Professional Services, Illumina
Genetic testing for clinical applications requires many components, such as physician and patient support, informed consent, secure data management, and many others. One of the most critical is an understanding of the analytical quality of the data that is being used to make clinical interpretations. As we move to an era of genomic testing, the importance of analytical validity increases because of the substantially increased potential for what can be learned from the same data. Illumina Clinical Services Laboratory has been performing whole genome sequencing in a CLIA certified, CAP accredited setting for nearly three years. This clinical test provides a comprehensive catalogue of variation across the genome, yielding >90% of the NCBI reportable reference genome and representing >96% of the exome. The quality of the calls is measured and monitored using a variety of metrics. Additionally, every genome is also analyzed on the Human 1M duo array, which genotypes over 1 million variants distributed across the genome, and the concordance to the sequencing results are compared.

We have compared the sequence data from multiple genomes, so that we are able to characterize regions and loci of particularly high quality as well as flag what may be unreliable. The quantitative nature of Next Generation Sequencing technologies allows us to evaluate the accuracy, sensitivity and specificity at the single base pair level, thus we report on the quality of every base that is called. As the scope of NGS applications expands in the clinical setting, robust and ongoing evaluations of quality are critical to ensure that NGS will realize its potential for improving patient care.
3:30 [Interactive Q&A Panel]
4:00 Workshop Concludes
Day 1 Day 2
Day 1 - Wednesday, May 30, 2012
7:00 Registration
7:55 Welcome & Opening Remarks
Pharmaco-omics
Richard Head, Genomics and Pathology Services, Washington University School of Medicine
KEYNOTE PRESENTATION
8:00 Pharmacogenomics: Beyond Biomarkers


Richard M. Weinshilboum, M.D.
Mary Lou and John H. Dasburg Professor in Cancer Genomics Research
Chair, Division of Clinical Pharmacology
Professor of Molecular Pharmacology & Experimental Therapeutics and Medicine
Mayo Clinic College of Medicine
Pharmacogenomics is the study of the role of inheritance in variation in drug response phenotypes. Those phenotypes can vary from serious adverse drug reactions at one end of the spectrum to lack of the desired therapeutic efficacy at the other. Pharmacogenetics has evolved into pharmacogenomics in the present post "Genome Project" world, with the application of techniques such as genome-wide association studies (GWAS) and whole genome sequencing (WGS) to perform pharmacogenomic studies. There is also increasing emphasis on the clinical translation of pharmacogenomics to the bedside but--in addition--pharmacogenomics is also discovery science. This presentation will focus on moving "beyond biomarkers" to place an emphasis on the use of pharmacogenomics to pursue functional explanations for pharmacogenomic observations as well as novel drug mechanisms. A series of examples will be used to illustrate this approach, focusing on the endocrine therapy of breast cancer, but the underlying principles will apply to all classes of drugs.
8:45 Moving Pharmacogenetics from the Laboratory to Clinical Practice
Tristan Sissung, P.h.D., Staff Scientist and Head of the Pharmacogenetics Core, Clinical Pharmacology Program, National Cancer Institute
The field of pharmacogenetics is rapidly expanding although we are still in the early stages of characterizing how genetics affects pharmacotherapy and applying this information in the clinic. According to the FDA, there are approximately 100 drugs with pharamcogenetic information in the label. Of these, six drugs have a boxed warning, indicating severe adverse effects in some users. In general, genes that have pharmacogenetic interactions fall into three major categories: (i) genes encoding enzymes that mediate drug disposition (i.e., ADME); (ii) genes encoding proteins that interact with drug activity; and (iii) genes encoding human leukocyte antigens that cause immune adverse drug reactions. Most of the initial studies in pharmacogenetics were candidate gene based; that is, these studies were largely hypothesis driven based on an understanding of drug pathways. More recently, pharmacogenetics findings have often been driven by larger scale discovery-science approaches, such as genome wide SNP studies or platform-based studies where multiple genetic factors that participate in pharmacology were studied. As nucleotide sequencing becomes more sophisticated and less expensive, large-scale efforts are more likely. Clinically, pharmacogenetics interactions generally either result in increased toxicity or reduced efficacy and either inform dose changes or choice of alternative therapy. However, in spite of accumulating evidence, there are few examples where pharmacogenetics-based dosing or treatment strategies are oft-used in the clinic.
9:10 Strengthening Genomic and Disease Inquiry with Metabolomics
Mike Milburn, CSO, Metabolon
Genome-wide association studies (GWAS) have identified many risk loci for complex diseases, but because of the multiple genes involved in many diseases and/or conditions the effect size is usually quite small. We recently published the largest human genome wide association study analyzing over 500 metabolites for over 3000 human blood samples (Nature, 477, pg. 37-41, 2011) and their concentration statistics relative to genotyping data. This study reported a comprehensive analysis of genotype-dependent metabolic phenotypes using a GWAS with non-targeted Global metabolomics investigating over 60 metabolic pathways. We identified 37 genetic loci associated with blood metabolite concentrations, of which 25 show effect sizes that are unusually high for GWAS and account for 10-60% differences in metabolite levels per allele copy. Our associations provide new functional insights for many disease-related associations that have been reported in previous studies, including those for cardiovascular and kidney disorders, type 2 diabetes, cancer, gout, venous thromboembolism and Crohn’s disease. This study clearly established the penetrance of genetic individuality to the measured metabolite levels even in blood and demonstrates the importance of strengthening genomic and disease inquiry with metabolomics.
9:35 Disease Biology-based, Post-genomic Approaches for Prognostic and Efficacy-predictive Biomarkers for Cancer
Peter Blume-Jensen, CSO, Metamark Genetics
The significant advances in cancer genetics in recent years have been met with only limited successes in progress in cancer treatment and care. To a great extent this is due to the challenges in identifying which specific genetic mutations are ‘drivers’ of the cancer phenotype. Metamark is taking a functional, mechanistic approach to identify the proteins and signaling pathways that are causally involved in the aggressive, metastatic cancer phenotype. Many of these ‘driver’ proteins are potential novel drug targets. Our scientific approach enables development of powerful prognostic and efficacy-predictive, protein-based, quantitative biomarkers.
10:00 Morning Break
10:30 Multiplex MRM-MS and iMALDI-MS for Personalized Medicine
Andrew Munk, MRM Proteomics Inc.
One focus of the University of Victoria – Genome British Columbia Proteomics Centre is the development and application of mass spectrometry (MS) based proteomics approaches towards clinical implication. In particular, we are focused on further development and improvement of two MS centric approaches: Multi-Reaction Monitoring (MRM) and immuno-MALDI (iMALDI) – both have great potential for biomarker validation and discovery and translation into clinical set ups since these approaches are rapid, highly specific and enable absolute and multiplex protein quantitation. We have developed a 67 protein MRM-assay for validation of numerous cardio-vascular disease (CVD) biomarkers (up to 1 ng/ml) in human blood plasma. We applied the MRM-assay in a medium scale project analyzing 250 blood samples in triplicate verifying a panel of proteins that are distinguishable between different CVDs. Furthermore, to address the clinical requirement, we have developed highly robust, sensitive and reproducible multiplex MRM approaches using new MS-technologies like the dual ion funnel technique from Agilent on-line coupled with high-flow UPLC.

The iMALDI technology is a combined approach of immuno-enrichment of peptides followed by MALDI-MS and has the capabilities to detect proteins at pg/ml concentration. An multiplex iMALDI assay to determine the plasma renin activity and angiotensin converting enzyme (ACE) by measuring the concentration of angiotensin I & II in blood has been developed into a clinical assay for hypertension. This iMALDI assay has great potential for personalized medicine and will replace the currently used radio-immunoassay in a Vancouver hospital due to its higher specificity, speed, accuracy and sensitivity at lower cost.

Benefits:
- Demonstrating the potential of MRM assays using normal LC flow rate and dual ion funnel technologies for accurate, sensitive and highly multiplex protein quantitation at high throughput
- New iMALDI assay for plasma renin & ACE activity being implemented in the clinic
10:55 Microfluidic 3D Culture as a Model for Personalized Therapeutics
Peter Tolias, Director, Bioinnovation Program, Stevens Institute of Technology
The precipitous drop in the cost and feasibility of performing whole genome DNA sequencing is opening new opportunities for personalized therapeutic intervention based on selection and treatment using drug combinations defined from analysis of the whole genome of any particular patient. This type of approach is well suited for cancer patients where perturbations in the cancer genome can be analyzed to define the key affected biochemical pathways and potential drug targets for which there are available drugs for treatment. We are addressing a current gap prior to treatment that involves experimental assessment of toxicology and efficacy of a predicted drug cocktail for a specific patient prior to actually prescribing the therapy. Our approach introduces in vitro assessment of the drug cocktail on a living biological specimen obtained from the patient grown through tissue engineering in a novel microfluidic 3D culturing platform. To this end, three different 3D culturing devices have been designed with controllable microenvironments that enable: (1) growth and maintenance of 3D tissues which are better at representing human physiology compared to cells grown in standard 2D cultures; (2) emulated microvascular, microlymphatic, and microinnervation network functions; (3) manageable microfluidic network design, control, and stability; (4) onboard optical fiber bundle networks for microendoscopic visualization of tissue cells and real-time microarray multiplex measurements of pharmacokinetic and pharmacodynamic parameters. These attributes make this novel platform technology amenable for evaluation of drug action prior to clinical trials, and development of new disease models for personalized medicine.
11:20 Accelerating Compound Specific Biomarker Research based on Multiple Technologies
Yoshiya Oda, Biomarkers and Personalized Medicine Core Function Unit, Eisai
Our unit mission is to utilize biomarkers to increase the value to patients of Eisai drug candidates. We have three types of biomarkers for drug development: 1) to achieve POM (proof-of-mechanism) for decision making for project teams in early clinical stage and determination of correct dosing (amount/schedule), 2) to identify most appropriate patients (patient stratification) for enhancement of success rate of projects and reduction of clinical study size, 3) to encourage patients/increase confidence of projects based on efficacy biomarkers. We have responsibility about these biomarker research, and our three main roles are 1) biomarker discovery to identify biomarker candidates and confirm biomarker candidates in early clinical stage, 2) biomarker assay development to increase sensitivity, selectivity and speed of assays, and to validate assay methods, 3) preclinical and clinical biomarker assay to provide flexible, quick and quality service to projects, and to work as a team with project members. To achieve these tasks, we have micro array systems for gene signatures, Taqman low density array systems and nanoString for accurate gene quantitation, Ion Torrent for gene mutation analysis, multiplexed ELISA systems for protein assays, mass spectrometry systems for proteomics and metabolomics, immunohistochemistry capability and bioinformatics to integrate those information. I will present some of our case studies in the conference.
11:45 Personalized Pharmacogenetics – The Forgotten Part of Personalized Medicine
Richard Head, Genomics and Pathology Services, Washington University School of Medicine
The clinical utility of next generation sequencing to guide personalized medicine is well established. Genomic analysis (whether by whole genome, exome, or focused panels) is used to identify sequence variants that underlie inherited constitutional diseases, as well as acquired sequence changes responsible for oncogenesis, and therapy is personalized based on selection of drugs known to target the identified mutations. However, a focus on constitutional or acquired drug targets ignores opportunities provided by genomic analysis of the loci that encode proteins controlling drug absorption, distribution, metabolism, and excretion (ADME) to adjust drug dosing for maximum therapeutic benefit. ADME screening can be used to identify patients with clinically significant alterations of target drug pharmacokinetics which may be associated with toxicity or an insufficient therapeutic effect at standard dosing levels. This presentation will explore the significance of genomic analysis of ADME loci, which, though currently a forgotten part of personalized medicine, will have an increasingly important role in basic science investigations, clinical trial design, and routine patient care. In particular, the talk with highlight the following key issues:

- What precedents demonstrate the clinical utility of personalized drug dosing?
- What genetic regions underlie ADME?
- Can next generation sequencing approaches be leveraged to address ADME issues to provide for personalized drug dosing?
- Is it likely that the current reimbursement environment will pay for ADME testing?
12:10 Lunch On Your Own
Advances in Genomic Medicine
Moderator: Paul Billings, Chief Medical Officer, Life Technologies
1:40 The Impact of Universal Clinical Sequencing on Patient Treatment
Paul Billings, Chief Medical Officer, Life Technologies
The development and implementation of microprocessor based next generation sequencing methods are rapidly speeding universal sequencing in clinical settings. The method’s simplicity, speed and accessibility are revolutionizing cancer care, the management of unknown conditions, and the diagnosis of certain infections. New targets are being identified, previously described disease drivers are finding new applications, and companion diagnostic products are being produced. This talk will review recent findings and suggest changes that are evolving,

Those attending will benefit by understanding:
- ION Torrent sequencing
- New clinical results
- Novel applications
- Clinical issues confronting this field
2:05 Integration of NGS Based Profiling into the Oncology Biomarker Identification Pipeline
Yair Benita, Senior Computation Biologist, Merck
Next generation sequencing (NGS) provides deep molecular insight into tumors at a low cost. However, the major challenge of employing this technology is the difficulty to interpret the vast amount of data obtained from cancer genomes and transcriptomes. In an effort to identify biomarkers of drug response we profiled hundreds of cell lines and exposed them to various drugs and drug combinations. In this talk I will discuss the challenges of interpreting NGS data and our current solutions for integrating this technology into the drug and biomarker development process. I will present our strategy to identify cancer driving somatic mutation, methods to link these mutations to drug response data and finally methods to project cell line profiles to tumors.
2:30 Integration of Profiling and NGS in Cancer Drug Discovery: Targets, Models, and Resistance
Paul Rejto, Director and Head of Computational Biology, Oncology Research Unit, Pfizer
Responders to targeted therapies are typically limited to select patient populations, motivating the need for precision medicine approaches in the clinic. The implications of tumor heterogeneity and differential drug response have important implications for preclinical drug discovery that can be addressed by the growing availability of NGS. In this presentation, practical examples where molecular characterization has enabled and accelerated cancer drug discovery programs in a large pharmaceutical company setting will be presented including target identification, model selection, and predictive biomarkers for patient segmentation.

Benefits:
- An NGS exome study of human gastric tumor samples identified novel cancer mutations and target candidates
- Molecular profiling of patient-derived xenografts and cell lines prioritized model systems for preclinical study
- Pharmacological testing of well-characterized model systems enabled the development of predictive biomarkers of drug response
- Resistance mechanisms have been identified by integrating profiling and NGS approaches
2:55 Afternoon Break
3:20 Informatics Platforms for Biomarker Research in the Next-Generation Sequencing Era
James Cai, Head, Disease & Translational Informatics, Roche
Treating the right patient with the right drug at the right time requires deep understanding of the disease mechanisms at the personal level. This personalized approach has become increasingly feasible with the rapid advances in the genomic technologies, especially in the Next-generation sequencing technologies. As the sequencing costs continue to drop at a rate faster than Moore’s law predicts, data management, analysis and interpretation have become and will continue to be the new bottleneck in the near future. How can we translate this massive amount of data into new targets and biomarkers for personalized treatment? In this talk, I will discuss the informatics strategies in addressing these challenges illustrated in a specific use case in Oncology, where hundreds of cancer cell lines have been profiled with exome-seq, RNA-seq, microarray gene expression measurements, copy number variations and compound sensitivity assays. In particular, audience can benefit from discussions in the following topics.

- A high-performance NGS pipeline that computes hundreds of exomes concurrently
- Validation of novel genetic variations
- A database and web application that provide integrated views of NGS and other genomic data
- What can we learn about the genomic landscape of cancer cell lines
- Finding response or resistance biomarkers as hypotheses for patient stratification
3:45

Using Systems Biology to Accelerate Oncology Drug Development
Johanna Lahdenranta, Principal Scientist, Merrimack Pharmaceuticals
This session will discuss how Merrimack uses mathematical models of cancer signaling pathways to design novel therapeutics, identify predictive biomarkers, and guide clinical development plans. By combining the knowledge gained from our biochemical model together with biomarker measurements from a large panel of archived tumors and clinical data from the literature, we simulated the effect of our lead oncology drug in a variety of cancer indications and used these simulations to help prioritize our clinical development plans. We will also discuss how we use our mathematical models to assess other targeted oncology drugs and determine which of these drugs should be combined with our therapies.
Identification and Validation of Drug Targets
 Moderator: Yair Benita, Senior Computation Biologist, Merck
4:15 Systematic, Genome-Scale Identification of Novel Drug Targets
Alex Gaither, Laboratory Head, Novartis Institute for Biomedical Research
The pharmaceutical industry faces a number of continual and growing challenges in bringing innovative new medicines to the clinic. The earliest challenge in the drug discovery process is the identification of novel, validated targets that have a high probability of providing both safe and effective therapeutic strategies. To this end, the The Department of Developmental and Molecular Pathways has focused on carrying out genome-scale gain and loss of function screens in mammalian systems that model disease processes in vitro. A focus on molecular pathways associated with human disease should help ensure the clinical relevance of identified targets. Examples of target identification from genome scale gain and loss of function screens will be presented.

Benefits of this talk:
-Description of approaches to comprehensively define regulators of human molecular signaling pathways.
-Evaluation of the utility of large scale RNAi approaches in mammalian cells.
-Comparison of different functional genomics approaches to target discover.
4:40 The Next Challenge – Translating the Cancer Genome into Impactful Drugs
Markus Warmuth, President and CEO H3 Biomedicine
Human Cancer evolves through a series of genetic and epigenetic events that allow a normal cell to become transforming and spread to distant organs. The past few years have seen a dramatic change in our understanding of the genetic basis of human cancer, mostly driven by the advances made in next generation sequencing technologies. Rapid and cost effective analysis of cancer genomes has started to not only bring new therapeutic targets to the surface, but also holds great promise in translating genetically target drugs and personalized medicines into the clinic. However, there are still many obstacles to overcome. As cancer genomic information increases on an exponential scale it has become clear that cancer genomes are complex, polyclonal and heterogeneous. In many cases it will not be possible to reduce the pathogenesis of a tumor type or subtype to a single driver activated by hotspot mutations. Instead, recent data suggest that mutations are scatter along genes and in pathways, posing the challenge of finding central and druggable nodes in the system. In addition, very little validation exists for many of the pathways emerging as frequently mutated and it is unclear if these pathways elicit oncogene addiction to a degree described for classical cancer genes (K-Ras, B-Raf, mutant EGFR, translocated kinases). Therefore, despite the promise of genetically targeted drugs, robust methods and platforms need to be established to drive validation of targets and there translation into the clinic.
5:05 The Application of Genetics to Support Drug Discovery and Development- Examples of Target Validation and Patient Stratification with a Look to the Future
Stephanie Chissoe, Director and Acting Head of Genetics, GlaxoSmithKline
Naturally occurring human genetic variation can provide a tool to predict drug response and understand drug target biology. As the collective pharmaceutical industry success rate for the development of novel medicines per investment dollar has declined over the past decade, there has been increased focus on enhanced target selection and validation to address failures to due lack of efficacy and on predicting drug response via safety and efficacy pharmacogenetics. This presentation will review recent examples of the application of genetics to support target validation and patient stratification, highlighting the challenges facing the field and opportunities for the future

Benifits:
- Increasing confidence in drug targets
- Integration of genetics with electronic health records
- Limitations of clinical trials
- Translation of genetics into clinical utility
- Academic-industry partnerships
5:30 Networking Reception
Day 1 Day 2
Day 2 - Thursday, May 31, 2011
Plenary Keynote Session
Moderator: Shidong Jia, Scientist, Oncology Biomarker Development Group, Genentech
KEYNOTE PRESENTATION
8:00 The Personal Genome Project - Open Access to Genome Sequences + Trait data



George Church, Ph.D.
Professor, Genetics; Director, Center for Computational Genetics
Harvard Medical School
The PGP enables open observation and critique of a large cohort "test-driving" comprehensive participatory personalized medicine. Since 2004, we have helped push the cost of reading and writing DNA (and biological systems) down by a million-fold (5-fold faster exponential than Moore's law) and enabled fully open-access human Genome+Environment=Trait (GET) data, stem cells, and clinical community curation/interpretation tools (Evidence.PersonalGenomes.org). This involves inherited genomes plus day-to-day genomic variation -- cancers, microbes, allergens, vaccines, & subcellular-resolution epigenomics. We are also sequencing centenarians and long-lived mammals. Benefits include human genome engineering technologies for personalized diagnostics as well as stem cell, synthetic organ, microbiome and immunome transplantation therapies.
8:45 KEYNOTE PRESENTATION
RNAi and Immortality: Recognition of Self/non-Self Nucleic Acids



Craig C Mello, Ph.D.
Nobel Laureate
Blais Professor in Molecular Medicine
University of Massachusetts Medical School
Howard Hughes Investigator
HHMI
Organisms exhibit a fascinating array of gene-silencing pathways, which have evolved, in part, to confront invasive nucleic acids such as transposons and viruses. Not surprisingly, these pathways are highly active in the germline and can be elicited upon the introduction of transgenes. A key question raised by the existence of these pathways is how do they distinguish self- from non-self nucleic acids? Evidence exists for a number of cues that might facilitate the recognition of foreign sequences including, copy-number sensing, sensing of unpaired DNA, or the sensing of aberrant RNA (e.g. dsRNA). Here we report on a remarkable silencing pathway that can permanently silence even single-copy transgenes. We show that the initiation of silencing depends on the piwi Argonaute PRG-1 and its genomically encoded piRNA cofactors. Our findings support a model in which PRG-1 scans for foreign sequences while two other Argonaute pathways serve as epigenetic memories of "self" and "non-self" RNAs. These findings suggest that organisms utilize RNAi-related mechanisms to keep inventory of all genes expressed in the germ-line, and to recognize and silence foreign genes.
9:30 Morning Break
Systems Biology for Therapeutic & Diagnostic Discovery
Moderator: Heinrich Roder, CTO and Director, Biodesix
10:15 Multivariate Tests for Clinical Proteomics
Heinrich Roder, CTO and Director, Biodesix
The discovery potential of proteomic research has opened new and exciting avenues in the understanding of molecular pathways, and thus created the hope of the development of clinically relevant biomarkers and eventually new clinically useful tests. New methodology has been developed to simultaneously measure the abundance of hundreds of proteins in simply-obtainable clinical samples like serum and plasma. Despite the progress, there are few tests that have taken advantage of the proteomic revolution, especially in the area of multi-variate tests that combine the measurement of multiple proteins for purposes of prognosis and prediction. Traditional single analyte tests are based on years of clinical discovery focused on the role of single markers, i.e. once a given biomarker has been established, validation reduces to the analytical problem of measuring the marker. In contrast, in multi-variate testing the clinical validity of a test needs to be established continuously with new clinical data. In this presentation I will summarize the problems arising in the validation of truly multi-variate tests, using as an example, VeriStrat®, a mass spectrometry based test that is used in NSCLC.

Benefits:
Combination of multiple markers into a single diagnostic
Clinical validation of multi-variate tests
Practical criteria for the analytical validation of multivariate tests
10:40 Systems biology in cancer immunotherapy: Applications in the understanding of mechanism of action and therapeutic response
Debraj GuhaThakurta, Sr. Scientist II & Group Leader, Dendreon Corporation
The talk will provide examples of the applications of high content platforms for understanding the mechanism of action and efficacy of an approved cellular immunotherapy, sipuleucel-T, for the treatment of asymptomatic or minimally symptomatic metastatic castrate-resistant prostate cancer (mCRPC). The treatment is designed to stimulate an immune response against prostate tumor cells expressing the prostate antigen PAP (prostatic acid phosphatase). We are applying high content platforms, such as protein and DNA microarrays, to study sipuleucel-T product characteristics and immune responses. Using protein microarrays that can assay for the presence of > 9,000 antibodies in a patient’s serum sample, we are studying the breadth of sipuleucel-T induced immune response, particularly that against additional tumor antigens. Results suggest that post-treatment antibody responses are developed against genes that are involved in cancer signaling pathways or over-expressed in prostate tumors. Using DNA microarrays, molecular comparison of differentially expressed genes in PBMCs indicates the activation and differentiation of APCs (antigen presenting cells) and T-cell subsets, as well as the induction of APC and T-cell associated cytokines in sipuleucel-T. These studies provide examples of genomic strategies that can aid in the development, mechanistic understanding, as well as the discovery of molecular markers associated with the efficacy of a cancer immunotherapy.
11:05 Immunosignaturing as a Platform for Diagnosis and Therapeutic Lead Discovery
Stephen Johnston, Director, Center for Innovations in Medicine, Biodesign Institute, Arizona State University
We have developed a new platform technology (Immunosignaturing) with applications to diagnosis, particularly early diagnosis, and to discovery of new therapeutic targets. It is based on the discovery that the antibody profile of a person is exquisitely sensitive to changes in health status, and the development of a scalable method of producing peptide arrays to read the antibody profile. The system is simple, inexpensive, robust and comprehensive. The same chip can be used for diagnosis of any disease in any organism. We have applied the platform to >20 different diseases and all have distinct immunosignatures, even in pre-symptomatic stages. Historical blood samples or samples sent through the standard mail are stable to for their immunosignatures and less than 0.1ul is required per assay. We have recently demonstrated that these signatures can be Deciphered to reveal proteins that are aberrantly or mal expressed in the defective cells, even at early stages of disease. Decipher may present a general platform for discovery of new therapeutic leads. HealthTell, LLC in collaboration with ASU is developing these platforms.

Benefits:
- Description of new diagnostic platform
- Method to develop diagnostics from historical blood samples
- Description of new peptide chip production technology
- Simple protocol for discovering new therapeutic targets.
11:30 Targeted Immuno-Affinity Proteomics: The Mass Spectrometric Immunoassay
Urban Kiernan, Senior Scientist, Thermo Fisher Scientific
Since the conception of proteomics some two decades ago, the field has undergone a massive evolutionary process in terms of technologies, methodologies, and goals. This evolution has seen a departure away from the original definition of the term and a steady progression towards rigorous clinical application. This impetus has placed a major focus on the coupling of high power mass spectrometry (MS) detection with upfront immuno-affinity protein purification. This combination provides the end user with the ability to perform enhanced multiplexed-type analyses for an added dimension in protein analytics and improved data content. Termed the Mass Spectrometric Immunoassay (MSIA), this natural combination of immuno-capture with MS detection, is already gaining acceptance as a viable alternative for clinical protein analysis as it has several assays that are now run in a CLIA approved setting. Moreover, this next generation of high content protein data is quickly becoming identified as clinically useful through the identification of several novel molecular biomarkers of disease. This presentation will describe this technical approach and provide specific examples regarding such unique high content data as it relates to and enhances biomarker discovery, therapeutic development, and disease state assessment.

Benefits of the Talk:
- Explain the advantages of such high content MSIA methodologies.
- Demonstrate the superior performance advantages of the described analytical platform.
- Introduce novel protein variation in disease.
- Describe the enhancement of biomarker clinical utility by using select protein variants of already known biomarkers.
11:55 Lunch Provided by GTC
1:00 Biomarkers: From Diagnosis to Optimal Care of LSD Patients
Kate Zhang, Director Therapeutic Protein Research, Genzyme, a Sanofi Company
The desired properties of a biomarker for lysosomal storage diseases (LSD) include specificity to the disease, correlation with disease burden, and its ability to reflect disease remission on therapy and conversely relapse of disease activity on sub-optimal therapy. In addition, the biomarker should be applicable to the majority of patients and there should be reliable assays as well as easy access to testing. Because LSDs are multisystemic, heterogeneous and complex conditions, biomarker discovery and subsequent assay development and validation require close collaboration of clinical assessment and statistical and analytical analysis of large number of patient samples. The presentation will report the LSD biomarker discover by proteomics and lipidomics and how biomarkers are qualified in clinical application.
1:25 Advanced Glycan Analysis Using HPLC-Chip/MS Technology
Rudolf Grimm, Director, Science & Technology, Agilent Technologies
A few years ago a fully automated and integrated analytical system consisting of a chip-based chromatography system in conjunction with time-of-flight, triple quadrupole and quadrupole time-of-flight mass spectrometers was introduced. The microfluidic HPLC-chips are made of laser ablated and laminated biocompatible polyimide films. Sample enrichment, separation and nanoelectrospray tips are fully integrated in the chip device. Chips with different functionality can be easily designed and developed for specific LC/MS applications. The system represents a breakthrough in nanoelectrospray MS sensitivity, chromatographic separation, reproducibility, sample throughput and ease of use.

In this presentation an update about the latest technical developments of the Chip-MS system will be provided. Applications of the Chip-MS system to the study of all classes of glycans (free glycans, N-glycans, O-glycans and glycosaminoglycans such as heparin) will be discussed. A new chip will be introduced that allows the fully automated analysis of N-glycans using an on-chip micro-reactor packed with immobilized PNGase F.
1:50 Protein Pathway Activation Mapping for Personalized Therapy: Applications at the Bedside
Emanuel Petricoin, Ph.D., Professor, Co-Director, Center for Applied Proteomics and Molecular Medicine, George Mason University
Proteomics is now entering into a new phase in the post-genome era. Since most molecularly targeted therapeutics target proteins, and since most clinical analytes that are used now and are in the pipeline for use for early detection and monitoring of cancer are proteins, proteomics is at the central nexus of molecular medicine. Cellular signaling pathways are a protein-based network, and the intended drug effect is to disrupt aberrant protein phosphorylation-based enzymatic activity, and epigenetic phenomena. Pharmacoproteomics, or the tailoring of therapy based on proteomic knowledge, will begin to take a central role in this process. A new type of protein array platform, the reverse-phase protein microarray, has begun to show enormous potential for providing detailed information about the state of the cellular ‘circuitry’ from small samples such as patient biopsy specimens. Coupled with a novel tissue fixative for molecular analysis, measurements of hundreds of specific phosphorylated proteins that constitute a novel patient-specific “drug target activation portrait” can be obtained at once from only a few thousand cells. Clinical utilization of this powerful platform is occurring at the bedside whereby key missing pieces of information concerning the state of the activated protein “circuitry” is being exploited for personalized therapy applications.
2:15 Gene Expression Markers in Blood that Predict Alzheimer’s Disease
Eric Yang, Informatics Scientist, Johnson & Johnson
Even with the existence of a disease modifying treatment for Alzheimer’s Disease, the best that we can hope for is the halting of disease progression, and not the reversal of cognitive impairment. Thus, it is of great interest to be able to detect Alzheimer’s Disease early in patients who are still cognitively normal. However, for us to accomplish this task, the test must be cheap as well as accurate. In collaboration with Kings College London, we can demonstrate that gene expression data obtained from a blood sample can provide signals that differentiate between people who are cognitively normal and people who have Alzheimer’s Disease. Furthermore, unlike prior work in blood diagnostics which required 50 or more genes/protein markers to distinguish between these two groups, we will show that a relatively small number of genes (11) are needed to differentiate between these two clusters. More interestingly, we can show that the cases where classifications by this gene expression fingerprint which do not agree with the underlying clinical diagnosis, there is evidence that the underlying clinical diagnosis is incorrect.

Benefits:
Identification Early Markers of Disease
Identification of Mechanisms Surrounding Disease
Review of Methodology
Overview of Biomarker state of the Art
2:40 Alzheimer Disease Biomarker Discovery and Validation Strategies
  Martin Latterich, Professor, Proteogenomics Research Institute for Systems Medicine
3:05 Conference Concludes
Day 1 Day 2
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