Day 1 - Thursday January 27, 2011

7:00

Registration & Breakfast

7:55

Chairman's Opening Remarks

Session I: Novel Technologies for Oncology Biomarker Discovery

8:00

Oncology Biomarker Discovery Technologies Today and Tomorrow

Thomas Li, Ph.D., FACB, FAAAAI, Senior Director, Technology Management, US Chief Technology Office, F. Hoffmann-La Roche Ltd

In this presentation, the past and present biomarker discovery technologies will be reviewed. Technology examples will be drawn from genomics, proteomics, glycomics, metabolomics and cellular analysis. Topics will include microarray, amplification, melting curve analysis, immunoassay, autoantibodies, antibody technology, multiplexing, mass spectrometry, immunohistochemistry, in situ hybridization, comparative genomic hybridization, copy number variation, sequencing, flow cytometry, digital imaging, bioinformatics and pathway analysis. Advances in automation, workflow and sample prep will also be covered. Finally future direction of biomarker discovery technologies will also be projected.

Benefits: Attendees will gain understanding on
The past and present biomarker technologies
Current limitation of biomarker technologies
Examples of biomarker discovery success story
Future direction of biomarker technology development

8:25

Tumor-Derived Secreted Proteins Lead to the Discovery of Circulating Biomarkers

Daniel Chelsky, Ph.D., Chief Scientific Officer, Caprion Proteomics

Circulating biomarkers can be identified by the direct analysis of biological fluids, such as plasma, CSF and urine. New tools enable the removal of high abundance proteins and the detection of disease-specific or drug-specific markers with very good sensitivity. Limitations still exist, notably the detection of the lowest abundance proteins as well as certainty around the tissue origin of the proteins of interest. These limitations can be overcome when diseased tissue is available, as in the case of surgically resected tumors. By isolation of the secretory apparatus from tissue samples, consisting mainly of the golgi and secretory vesicles, proteins destined for secretion into the blood can be detected and identified by mass spectrometry while they are still highly concentrated and enriched. Comparisons can then be made between tumor and adjacent normal tissue to identify proteins that are present at higher levels in the tumor. These candidate markers can then be quantified in plasma samples, either directly or following antibody enrichment. A high degree of correlation is found to exist between differentially expressed proteins identified in the tissue and their differential expression in the blood, making this approach a very powerful tool.

Examples of successful cancer biomarker discovery studies in plasma and CSF
Analysis of the tumor “secretome” to identify circulating biomarkers
Approaches to validation of candidate biomarkers by MRM

8:50

Immunosignatures as a New, Simple Sheap Platform for Cancer Diagnosis

Stephen A. Johnston, Ph.D., Director, Center for Innovations in Medicine,Professor, School of Life Sciences, The Biodesign Institute, Arizona State University

The field of cancer biomarker discovery has been notably unsuccessful, particularly considering the amount invested. We have developed a new method for diagnosis, Immmunosignaturing, that may improve on traditional biomarkers. The underlying idea is that the population of antibodies in an individual can serve as a biomarker of health status. Further, the antibodies change in response to the onset of disease and that this change has common features among individuals with the same disease. We measure these antibody profiles by applying a drop of serum or saliva to a slide on which 10k peptides have been spotted. Each peptide is of a unique, but randomly comprised, sequence of 20 aa length. The serum is washed off and the bound antibodies detected with a secondary antibody for the isotype of interest. Because the antibodies are so stable, historical serum samples can be used. We have applied this technique to several types of cancer including breast, glioma and pancreatic and find that each cancer elicits a different immunosignature. Surprisingly, the signature consists of reactivities that go down as well as up relative to healthy controls. Our goal is to transform this system into one widely used for cancer diagnosis. To enable this transition we have launched a project to produce immunosignaturing chips by computer chip, mask-based lithography. Besides allowing making 1M peptides per chip, this technology would provide the advantages of scale, standardization and cost enjoyed by computer chip production.

Benefits to Attendees:
- Immunosignaturing uses the total serum antibody content as a “biomarker”
- How and why it works will be demonstrated
- The same chip is used for all diseases
- Demonstrations of its application to cancer will be given

9:15

High-Content Protein Microarrays for Biomarker Discovery

Lisa Freeman-Cook, Ph.D., Senior R&D Manager, Life Technologies

The diagnostic value of serum autoantibodies for many diseases, including cancer, diabetes, and autoimmune disorders is well established. Identifying the antigens that elicit an autoimmune response can yield panels of biomarkers that can be used as classifiers for particular diseases, disease stages, or as predictors of patient outcomes. High content protein arrays have been used to identify autoantibody biomarkers for multiples disease states, including Systemic Lupus Erythematosus (SLE), transplant rejection, and cancer. Here we will discuss two studies which utilized protein microarrays comprised of up to 9,000 purified full-length human proteins to evaluate immunological profiles across panels of serum samples to identify biomarkers for SLE diagnosis and early detection of colorectal cancer. Known SLE markers were identified and validated as expected, and 50 previously unreported markers were identified with potential clinical utility. Forty-six markers were identified for early detection of colorectal cancer, and we will describe validation of these markers. These studies demonstrate some of the challenges and successes of typical biomarker discovery studies. Here we will demonstrate the importance of good study design, sample size selection, need for appropriate methods of statistical analysis and challenges in developing validation tools.

Attendees will learn:
1) The current state of high content protein microarray technology
2) The utility of high content protein microarrays for autoantibody biomarker discovery
3) The importance of good study design and statistical analysis in biomarker discovery
4) Validation strategies for autoantibody biomarkers

9:40

Single Cell Network Profiling Technology and Applications in Clinical Medicine and Drug Development

Diane Longo, Scientist, Nodality

Given the complex heterogeneity of AML as well as the availability of newly approved and investigational therapeutic agents, a greater understanding of disease biology is needed to chart disease progression and assist in the optimal selection of therapeutic agents on an individual patient basis.

Single Cell Network Profiling (SCNP) is an approach for analyzing and interpreting post-translational protein modifications (e.g. phosphorylation, acetylation etc.) at the single cell level. Using viable cells, measurements are made on endogenous proteins before and after exposure to extracellular modulators such as growth factors, cytokines or drugs which are chosen to evoke cellular responses that echo how the signaling system is normally, or abnormally, patterned. The proteomic readout in the presence or absence of a specific modulator is termed a “signaling node”. Signaling nodes are evaluated within cells from samples that have associated relevant clinical information regarding response to the therapy of interest. Multivariate analysis can then be performed to create predictive models that can be validated in subsequent independent studies.

Results from studies conducted to assess the value of SCNP in guiding AML clinical management including prediction of response to standard induction therapy, patient-specific relapse risk, and response to novel therapies in AML will be discussed.

Benefits for attendees:
- Single Cell Network Profiling (SCNP) approach
- Industrialization of the assay for informing clinical decisions
- Application of SCNP to AML
- Prediction of AML patient response to standard induction chemotherapy and novel therapeutics

[FEATURED PRESENTATION]

10:05

Identification of Tumor Biomarkers Associated with Clinical Benefit to MAGE-A3 Antigen-Specific Immunotherapy in Melanoma and NSCLC

Jamila Louahed, Ph.D., Director, Head of Research and Development, Cancer Immunotherapeutics, GlaxoSmithKline Biologicals SA

10:30

Shabnam Tangri, Ph.D., Director, Clinical Science and Technology, Biogen Idec

10:55

Networking and Reception Break

Session II: Patient Selection and Stratification using Biomarkers

11:25

Multidimensionality of Oncology Biomarkers: Time for a Paradigm Shift

Alan Spatz, M.D., Director, Pathology Department, Jewish General Hospital, Professor of Pathology and Oncology, McGill University

The definition of cancer is operational and flexible. The diagnosis is often based on the degree of deviation from the “ideal” benign situation and it is assumed that the morphological deviation reflects the risk continuum. As a result, there is a permanent and fluid interaction between diagnostic and prognostic biomarkers. Cancer diagnosis and prognostication overlap; the dichotomous assessment of benignity versus malignancy is artificial and in many instances does not reflect the tumor biology nor the clinical situation.
The interaction between prognostic and predictive biomarkers is more complex. Prognostic biomarkers need large annotated repositories built up from any cohort of patients, whereas predictive biomarkers can only be discovered from clinical trial repositories. Therefore, due to the segmentation of clinical trial tissue banks and databases, identifying and validating a combination of predictive biomarkers is much more challenging than validating a combination of prognostic biomarkers -such as a grading system. This represents a major obstacle to the development of multi-modal targeted therapies.
This presentation suggests it is time to replace single measurements and clusterization based on single biomarkers breakpoints by multidimensional data, to build out tools to identify optimal biomarkers combinations and platforms such scientists coming from different fields can better work to generate high-quality integrated data.

11:50

Integrated Analysis of Lung Cancer Reveals Molecular Architecture and Suggests Selection Criteria for Treatment with Targeted Therapies

Andrey Loboda, Ph.D., Oncology Molecular Profiling, Merck Laboratories

While multiple targeted therapies are currently undergoing clinical development, knowledge of the molecular determinants of response to these inhibitors continues to emerge. We will describe an approach that combines integrated analysis of human disease biology with preclinical models of efficacy, resulting in a molecular portrait that enables the identification of candidate responder populations in lung cancer. We will present an integrated, genome-wide analysis of mRNA, DNA copy number, and somatic mutation profiles across approximately human 500 lung cancers and 100 lung cancer cell lines. This analysis reveals molecular subtypes, deregulated pathways within subtypes, likely drivers of deregulated pathways, and the prevalence of these biomarkers across lung cancers. By combining these results with drug response data from pre-clinical model systems, a molecular classification scheme emerges that can be used to guide the development of targeted therapeutics. This systems-level view will contribute to the understanding and personalized treatment of lung cancer.

12:15

A Novel Approach Utilizing Urinary Biomarkers for Managing Bladder Cancer Patients

Anthony P. Shuber, Chief Technology Officer, Co-Founder, Predictive Biosciences

We have recently reported the development of a non-invasive diagnostic assay using urinary Matrix Metalloproteinases (MMPs). Using a novel approach called Clinical Intervention Determining Diagnostic (CIDD), we identified with high confidence those patients without bladder cancer. In order to refine this assay and maximize Negative Predictive Value (NPV) driven by sensitivity, we have added additional protein markers and developed a Real Time PCR assay to detect FGFR3 mutations in urine. FGFR3 mutations are associated with low-stage non-invasive tumors where sensitivity reaches ~70%. FGFR3 mutations have been detected in the urine of bladder cancer patients, making this an attractive non-invasive DNA marker.
We measured and compared MMP-2 and MMP-9 levels by ELISA and ADAM12 by western in a cohort of 181 patients undergoing monitoring for bladder cancer recurrence, 25 of which had a confirmed recurrence. We are currently analyzing this cohort for the presence of eight FGFR3 mutations, and have modeled results to ultimately combine both the protein and DNA analyses into one assay. Using the prevalence of FGFR3 mutations in the urine of bladder cancer patients from other studies, we simulated FGFR3 detection in these samples. We then tested for MMP-2 and ADAM12 protein levels. Using these 3 additional markers sensitivity increased to 96% resulting in the identification of 31% of patients who do not have cancer at 98% NPV.
The novel Multi-Analyte Diagnostic Readout (MADR) concept described here combines the best performance characteristics of protein biomarkers and DNA biomarkers into one assay for optimal clinical performance.
We believe this is the first demonstration of combining both DNA and protein biomarkers into a single diagnostic assay. This approach combines the unique properties of both analytes; The inherent specificity associated with DNA, and the ability to achieve high sensitivities with protein markers.

12:40

Denise Uettwiller-Geiger, Ph.D., Director, John T. Mather Memorial Hospital

1:05

Lunch On Your Own

Session III:  Biomarkers and Cancer Personalized Medicine

2:35

Myla Lai-Goldman, M.D., Chief Executive Officer, CancerGuide Diagnostics

[FEATURED PRESENTATION]

3:00

Those Biomarkers Come from Biospecimens: Garbage In, Garbage Out!

Carolyn Compton, M.D., Ph.D., Director, Office of Biorepositories and Biospecimen Research (OBBR), National Cancer Institute

Human biospecimens, such as tissue or blood, are the principal sources of molecular data from patients. Human biospecimens of sufficient quality to meet the demands of the state-of-the-art analysis technologies are essential for the accurate identification of molecular targets for drug development, disease diagnosis, and prevention; characterization of biologic variations that determine drug efficacy and drug toxicity; identification of markers for susceptibility, screening, and reoccurrence; development of molecular-based disease taxonomies; elucidation of molecular mechanisms of disease; and validation new therapeutics and diagnostics.
The increased molecular analysis capabilities of a technology-rich era have raised the bar for the quality of biospecimens to be analyzed and the biomolecular analytes (e.g., RNAs, DNA, chromatin, etc.) derived from them. Individual molecular species derived from the biospecimen must be of high, consistent quality to ensure that the molecular-analysis data is reliable. When the analytes (”biomarkers”) come from human biospecimens, the quality of the biospecimen itself is a precondition of derivative analyte quality.
Biospecimen preanalytical variations are known to affect molecular assay readouts. As viable entities, biospecimens react to their environment until they are stabilized and/or preserved and thereafter also may be subject to molecular alterations or degradation. The biology of the biospecimen may be demonstrably influenced by variations at any stage in the lifecycle of the biospecimen, from the medical condition and pharmaceutical exposures of the patient of origin to the conditions under which the stabilized biospecimen is stored until it is assayed. Ensuring biospecimen quality involves controlling preanalytical variation so that the biology of the sample being analyzed approximates the biology of the disease in vivo as closely as possible. When particular preanalytical variables cannot be controlled, they should be recorded to enable variable-adjusted analysis data interpretation. The essential principle of molecular analysis is “garbage in, garbage out,” meaning that the integrity of the analysis data reflects the quality of the analytes from which it is derived.

Learning benefits:
1) how pre-analytical variables change biospecimen molecular composition.
2) how pre-analytical variables change biospecimen molecular quality.
3) how either can lead to misinterpretation of artifact as a biomarker.
4) how to approach a solution to these issues.

3:25

Pioneering Personalized Healthcare through Pharma Partnering: A Case Study in Companion Diagnostic Co-Development

Stephen Little, Ph.D., Vice President, Personalized Healthcare, QIAGEN

QIAGEN (formerly DxS Ltd) has established itself as the market leader in the successful co-development of drug-diagnostic solutions with pharmaceutical partners. QIAGEN has a considerable portfolio of over 15 ongoing collaborations with drug giants such as Amgen, AstraZeneca, Bristol-Myers Squibb and ImClone Systems, Pfizer and Boehringer Ingelheim.

This presentation will outline the current state of the personalized healthcare industry, investigating the regulatory and commercial hurdles involved in bringing a companion diagnostic to market and the importance of pharma partnering during clinical development as a way to overcome these hurdles.

Focusing on two of QIAGEN’s key experiences with companion diagnostic development for cancer, the presentation will look first at the KRAS story and the challenge of producing the first companion diagnostic of its kind – the TheraScreen®: K-RAS Mutation Kit to predict patient response to metastatic colorectal cancer therapies Vectibix® (Amgen) and Erbitux® (BMS/Imclone Sysytems) based on the mutation status of the KRAS oncogene.

Next, it will examine the importance of another companion diagnostic, the TheraScreen: EGFR29 Mutation Test Kit and its role in facilitating the marketing approval of AstraZeneca’s non-small cell lung cancer drug IRESSA® in Europe for EGFR mutation positive patients.

The importance of independent partners for the co-development of drug and diagnostic:

• Obstacles to bringing companion diagnostic tests to market and how QIAGEN has overcome them
• Why should pharma use a diagnostic partner?
• The Pharma companies’ ‘wish list’ when selecting a companion diagnostic partner
• What the future holds for personalized healthcare

3:50

Networking and Reception Break

4:15

Wim Van Criekinge, Ph.D., Vice President, Biomarker and Pharmacogenomics Research, Oncomethylome

4:40

Breast Cancer Gene Expression Signatures – Utility Beyond Predicting Metastatic Potential and Tamoxifen Response

Andrew Grupe, Ph.D., Senior Director, Pharmacogenomics, Celera

Prognostic expression signatures can aid in selecting the most appropriate treatment regimen relative to the expected course of disease. Expression signatures with different gene sets have been shown to have similar performance. Correlating breast cancer signatures with drug response in widely used cell lines that model human tumors and in isogenic cell lines with defined oncogenic mutations provides test systems to assess the predictive power of these signatures for novel therapeutics during the early stages of drug development. Here we will describe a signature that is prognostic of distant metastasis formation and predictive of tamoxifen treatment in breast cancer patients. Comparisons indicate that it correlates with other reported signatures, thereby suggesting similar clinical utility. Furthermore we will describe data from cell line studies, including cell lines with engineered oncogenic mutations, which assess the signature’s utility for targeted treatments.

Attendees will learn:
-Improving individual treatment response by profiling patient tumor tissue with predictive biomarkers
-Gaining molecular insight into drug response
-Correlation between different metastasis scores
-Opportunities for using cell lines and expression scores to advance personalized medicine
       -Pre-clinical information from treatment studies
       -Isogenic cell lines with defined oncogenic mutations

5:05

Networking and Reception Break

Day 2 - Friday January 28, 2011

7:30

Registration & Breakfast

7:55

Chairman's Opening Remarks

Session III:  Biomarkers and Cancer Personalized Medicine Cont.

8:00

Biological Target for Predicting and Monitoring Disease Recurrence in Oncology

Ginette Serrero, Ph.D., Chief Executive Officer, A&G Pharmaceutical

Applying biological screen for target discovery has been a very powerful approach to identify targets in oncology that have therapeutic and diagnostic applications as solutions in personalized medicine. Using this approach we have discovered a novel biomarker overexpressed and secreted by breast tumors and plays a critical role in breast tumorigenesis and acquisition to resistance to therapy. Diagnostic and therapeutic development is presently carried out using this target at A&G Pharmaceutical. In particular, a tissue and blood tests were developed to detect this biomarker in breast biopsies as well as in serum of breast cancer patients. Training trial followed by a validation clinical study totaling more than 500 patients have demonstrated and validated that tissue expression of this biomarker was a predictor of recurrence independent of tumor size, tumor grade, disease stage and lymph node status. On-going prospective clinical studies examine whether measurement of circulating level of biomarker can be used for real time monitoring of recurrence. These data and the Impact of biological target discovery on personalized medicine in oncology will be presented.

Audience will gain knowledge about a novel biomarker, will learn the development of a diagnostic kit for breast cancer, about the establishment of a training study and a validation study to establish and then demonstrate clinical utility. They will also be presented with strategy to put together a study leading to an FDA diagnostic application. Our presentation will also cover topic of theranostic target for the development of novel solutions in personalized medicine.

8:25

Personalized Tumor Profiles through Sequencing: Initial Efforts and Experiences

Ali Torkamani, Ph.D., Assistant Professor, Molecular and Experimental Medicine, Scripps Research Institute

At Scripps Translational Science Institute, we have initiated a human tumor sequencing program aimed at providing personalized tumor mutational data back to oncologists. The program is in its early stages with a small handful of patient tumor and normal tissue pairs sequenced. Although the clinical consequences most mutations are unknown, a large body of knowledge exists to bring us closer to identifying the right course of treatment not only for each type of cancer, but for each individual patient. As an ongoing project, we will be developing databases that catalogue the compendium of genomic changes, defining a range of different cancer types. These data will eventually serve as individualized biomarkers for patient care and potentially for the identification of actionable drug targets. I will share some of our initial experiences with developing this program.

8:50

[Oral Presentation from Exemplary Submitted Abstracts]

To be considered for an oral presentation, please submit an abstract here

Session IV: Regulatory Aspects of Biomarker Test Development

[FEATURED PRESENTATION]

9:20

Stefano Bertuzzi, Director of Science Policy, Office of the Director, NIH

9:45

Biomarkers and Immune Monitoring in Cancer Vaccines and Immunotherapy Trials

Raj K. Puri, M.D., Ph.D., Director, Division of Cellular and Gene TherapiesOffice of Cellular,Tissue and Gene Therapies, FDA/CBER

Session V:  Biomarker Design & Identification

10:10

Serum and Urine Multibiomarker Profiles for Cancer Detection and Diagnosis

Anna Lokshin, Ph.D., Associate Professor, University of Pittsburgh

The measurement of biomarkers present in the bodily fluids of cancer patients represents an important avenue for the development of minimally invasive tests to predict tumorigenesis, disease recurrence, or treatment response. We performed an analysis of biomarkers present in the urine and serum of patients diagnosed with ovarian, pancreatic, and breast cancer utilizing multiplexed bead-based immunoassays developed for the Luminex® xMAP® platform. Ovarian and breast cancer patients were compared to matched healthy controls while the pancreatic cancer patients were compared to a group of patients diagnosed with benign pancreatic conditions. Each case/control group was tested for 15-98 biomarkers identified as informative for each cancer type through previous population-based analyses of serum biomarkers. In our analysis, nearly all of the tested biomarkers were detectable in urine and many of the biomarkers exhibited mean relative differences of greater magnitude in urine versus serum. Our multivariate analysis identified several urine multimarker panels capable of discriminating the cancer from the control groups with high sensitivity and specificity. The use of a 4-biomarker panel comprised of 3 urine biomarkers and one serum biomarker resulted in the discrimination of ovarian cancer patients from healthy controls with a sensitivity of 100% at 95% specificity. For the ovarian and pancreatic cancer comparisons, urine/serum multimarker panels outperformed the best serum biomarker panels identified. A urine 3-biomarker panel was identified in the breast cancer comparison that demonstrated a high discriminatory power in both training and validation sample sets. Our results support the use of urine biomarkers as alternatives and/or companions to serum biomarkers for the diagnosis of selected human cancers.
Urine could potentially become bodily fluid of choice for first line cancer screening.

10:35

Networking and Reception Break

11:50

GPI Anchors: Much More than an Alternative Strategy for Cell Surface Presentation

Nathalie Scholler, M.D., Ph.D., Assistant Professor, University of Pennsylvania

Tumors polarize their microenvironment to escape immune-mediated destruction and promote their growth. Tumor-associated macrophages (TAM) respond to microenvironmental signals by developing an alternative phenotype (M2) with altered cytokine profile and overexpression of scavenger (SR) and mannose (MR) receptors. Biomarkers able to track such modifications would help detecting early changes in the tumor microenvironment and disease aggressiveness. Various cancer biomarkers such as mesothelin, CEA and folate receptor are GPI-anchored proteins, but their soluble forms have not been linked to any specific functions. Because GPI-anchors expose free mannose residues after cleavage, we hypothesized that these residues could bind to MR and alter macrophage polarization.
We established an in vitro model system to assess macrophage phenotype changes triggered by tumor-release mesothelin in medium or in the presence of three novel anti-MR recombinant antibodies (anti-MR scFv). We found that tumor-released mesothelin bound to macrophages in presence of calcium and that anti-MR scFv could block the binding, demonstrating that mesothelin binds to macrophages via GPI-anchor/MR interaction. Furthermore, one of the anti-MR scFv prevented tumor-induced macrophage switch towards M2 phenotype. We also monitored ovarian cancer tumor growth in mice genetically depleted for mannose receptor (MRKO). MRKO mice were injected intraperitoneally with luminescent-labeled ovarian cancer cells that overexpressed mesothelin. Tumor growth rates and ascites formation were reduced in MRKO. We propose that the quantification of soluble GPI anchor proteins in fluids could be correlated to M2/M1 ratios and disease aggressiveness, and that compounds able to block GPI-anchor/MR interaction could hinder tumor-mediated macrophage switch and inhibit tumor growth.

BENEFITS: Learn about the latest updates on ovarian cancer tumor microenvironment; a novel interaction between macrophages and GPI anchored proteins; a novel functional role of GPI anchored proteins in cancer and their possible use as biomarkers; and a novel mouse model to study the role of M2 macrophages in cancer

12:15

Development for Personalized Cancer Therapy– Challenges and Opportunities

Andrew E. Schade, M.D. ,Ph.D., Medical Advisor, Eli Lilly and Co.

As more targeted cancer therapeutic agents become established in clinical practice, there will be a growing need to define the patient populations most likely to respond to treatment. Utilizing the most appropriate therapeutic agents for a particular patient increases the benefit to risk ratio while minimizing non-efficacious treatments. This has already been seen in colorectal cancer, lung cancer, and breast cancer with the increasing use of KRAS testing, non-squamous histology, and ER/PR/HER2 status, respectively, to drive therapeutic decisions. In addition, the development of novel agents can be accelerated by identifying those patients most likely to respond to new medicines. Biomarkers can help inform two key questions in drug development: (1) Is this compound a potential drug (pharmacodynamic biomarkers), and (2) Who should get this drug (patient stratification markers/companion diagnostics). Developing robust clinical assays to detect biomarkers constitutes a significant challenge in drug development. A detailed framework for approaching biomarker development will be presented, with specific examples of assays put into practice for assessing the PI3K/AKT signaling network in clinical trials.
Benefits:
- Robust analytical validation of tissue-based biomarkers will be presented
- Opportunities and challenges with using surrogate tissues will be examined
- Role of circulating tumor cells in drug development will be discussed

12:40

[Oral Presentation from Exemplary Submitted Abstracts]

To be considered for an oral presentation, please submit an abstract here

1:05

Lunch

2:35

Dave S.B. Hoon, Director,  Department Molecular Oncology, John Wayne Cancer Institute

3:00

Craig Davis, Director,  Translational Oncology, Pfizer

3:30

Conference Concludes