Archived Content

Track 5: Biomarkers for Patient Selection 


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Tuesday, May 7


12:15-1:45 Conference Registration


Biomarkers to Diagnostics 

1:45-1:50 Chairperson’s Opening Remarks

1:50-2:15 Will Regulation of Laboratory-Developed Tests Stifle Innovation?

Alan Mertz, President, American Clinical Laboratory Association

2:15-2:40 From Biomarker Research to Diagnostic Development—Our Challenges

Yoshi Oda, Ph.D., President, Biomarkers and Personalized Medicine Core Function Unit, Eisai

Biomarkers play important roles for drug development as a part of translational research. Several examples about biomarkers for 1) the evidence of target engagement, 2) patient stratification, 3) drug efficacy and 4) disease diagnostics will be discussed.

2:40-3:45 Refreshment Break in the Exhibit Hall with Poster Viewing


Molecular Profiling of Tumor Heterogeneity to Guide Therapy 

3:45-3:50 Chairperson’s Remarks

3:50-4:15 Liquid Biopsies to Monitor Response and Resistance to Targeted Therapies

Luis Alberto Diaz, M.D., Associate Professor of Oncology, Johns Hopkins Sidney Kimmel Comprehensive Cancer Center

The simplest hypothesis to account for the development of resistance to EGFR blockade is that rare cells with KRAS mutations pre-exist at low levels in tumors with ostensibly wild-type KRAS genes. Although this hypothesis would seem readily testable, there is no evidence in pre-clinical models to support it, nor is there data from patients. To test this hypothesis, we determined whether mutant KRAS DNA could be detected in the circulation of 28 patients receiving monotherapy with panitumumab, a therapeutic anti-EGFR antibody. The results suggest that the emergence of KRAS mutations is a mediator of acquired resistance to EGFR blockade and that these mutations can be detected in a non-invasive manner. They explain why solid tumors develop resistance to targeted therapies in a highly reproducible fashion.

4:15-4:40 Application of Clinical Tumor Genotyping in Targeted Cancer Therapy

Darrell R. Borger, Ph.D., Co-Director, Translational Research Laboratory, Massachusetts General Hospital Cancer Center

Multiplexed tumor genotyping has been offered as a physician-ordered clinical test at a major U.S. cancer center. Over 3,000 patients have been evaluated and these new capabilities have fostered a genotype-directed approach to clinical trial design. By testing a broad spectrum of tumor types, new molecular signatures have been revealed and mechanisms of de novo and acquired resistance to targeted therapies have been uncovered. This has provided the foundation for expanding clinical cancer genotyping approaches for personalizing cancer care.

4:40-5:05 Quantitative Tumor Protein Profiling for Therapy-Relevant Stratification of Breast Cancer Patients

Hallgeir Rui, M.D., Ph.D., Professor, Cancer Biology, Medical Oncology and Pathology; Scientific Director, Jefferson Breast Care Center; Program Leader, Biology of Breast Cancer, Kimmel Cancer Center; Co-Director, Pathology Translational Research Core, Thomas Jefferson University

Breast cancer is a heterogeneous group of malignancies driven by diverse oncogenic pathways. Ongoing consortium efforts are to map breast cancer subtypes at high resolution based on quantitative immunofluorescence (QIF) profiling of druggable target proteins within carcinoma cells of a panel of 5,000 untreated primary breast cancer specimens. Progress with prolactin-receptor-Jak-Stat pathway profiling will be highlighted using complementary QIF technologies. Utility of resulting protein-based breast cancer subclassification maps for rational recruitment of patients into biomarker-driven, adaptive clinical trials will be discussed.

5:05-5:30 Clinical Validation of Predictive Biomarkers and Next-Generation Personalized Medicine Treatment Strategies Incorporating Genetic Dynamics

Robert A. Beckman, M.D., External Faculty, Center for Evolution and Cancer, Helen Diller Family Cancer Center, University of California at San Francisco; Executive Director, Clinical Development Oncology, Daiichi Sankyo Pharma Development

The future of oncology drug development lies in personalized therapy using predictive biomarkers. However, examples of the failure of predictive biomarkers also exist. In these cases the use of biomarkers increased the costs, complexity and duration of clinical trials, and narrowed the treated population unnecessarily. We present methods to adaptively integrate predictive biomarkers into clinical programs in a data-driven manner, wherein these biomarkers are emphasized in exact proportion to the evidence supporting their clinical predictive value. Next-generation personalized treatment strategies, which emphasize tumor heterogeneity, evolutionary dynamics and possible future tumor states, will also be presented.

6:00-9:00 Dinner Course

Laboratory-Developed Tests

(Separate registration required)



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