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Clinical Genomics for Cancer Diagnostics
Clinical Genomics for
Cancer Diagnostics
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Clinical Genomics for Cancer Diagnostics - Day 1


Conference Proceeding CD Now Available
  • Speaker Presentations
  • Poster Abstracts
  • and More!

Day 1 | Day 2 


MONDAY, SEPTEMBER 23



PRE-CONFERENCE SHORT COURSE

9:00 am - 12:00 pm Next-Generation Sequencing for Clinical Cancer Diagnostics*

  • Implementation challenges
  • Bioinformatics - working with and analyzing big data
  • Special considerations for cancer management

Instructors:

Robert D. Daber, Ph.D., Technical Director, Clinical Genomics, Center for Personalized Diagnostics, Perelman School of Medicine, University of Pennsylvania

Jennifer Morrissette, Ph.D., Director, Cancer Cytogenetics, Center for Personalized Diagnostics, University of Pennsylvania

Jeremy Segal, M.D., Ph.D., Assistant Professor, Pathology, University of Chicago

 

View Detailed Agenda 

 

*Separate Registration Required

 

 

MAIN CONFERENCE

 

INTERROGATING CANCER GENES WITH NGS-BASED APPROACHES 

1:25 pm Chairperson's Remarks

Trever Bivona, M.D., Ph.D., Assistant Professor, Medicine/Hematology-Oncology, University of California, San Francisco

» KEYNOTE PRESENTATION:

1:30 Integrated Genomic Data Informs Cancer Treatment

/uploadedImages/Conferences/Conferences/cgn/Elaine-Mardis.jpgElaine R. Mardis, Ph.D., Professor, Genetics and Molecular Microbiology; Co-Director, The Genome Institute, Washington University School of Medicine at Washington University Medical Center

Next-generation sequencing instruments and advanced bioinformatic data analysis approaches have enabled unprecedented exploration of the human genome, especially in the comparison of tumor to normal genomes from the same patient. While there has been an enormous amount of discovery work that has characterized the genomic landscape of both solid and liquid cancers, the translation of these approaches to clinical practice has been minimal. My talk will explore our efforts to pursue the use of cancer genomics on an individual patient basis, to provide therapeutic options for consideration by the patient and the treating oncologist. I will provide several vignettes from our work to-date, and make an argument for the broader application of this approach toward clinical utility.

2:00 Solving the "Big Data" Challenge at the Interface of Science and Medicine

Mick Correll, COO, GenoSpace LLC

The sequencing of the human genome promised to open new ways of understanding human disease. New sequencing technologies, which have driven the cost of whole-genome sequencing to a few thousands of dollars have begun to make this vision a reality. However, while genomic data has rapidly become a commodity, solving the problem of collecting, managing, analyzing, and interpreting it--as well as delivering it to the appropriate individuals in the health care ecosystem--was a largely unmet challenge. The solution to this problem sits at the interface between science and medicine, each of which have unique needs and require distinct solutions. Here, we present solutions that address this challenge today and which can scale to address the challenges of tomorrow.

Agilent Technologies2:30 Characterizing Cancer Driver Gene Mutations in Metastatic Brain Tumors

Aliccia Bollig-Fischer, Ph.D., Assistant Professor, Oncology, Associate Director, Genomics Core Karmanos Cancer Institute, Wayne State University

Narrowing down results from sample analyses to the subset of data that are likely to have clinical research relevance, ongoing research, and hypotheses generation is especially important and useful when conducting a study that does not include a vast number of samples. This eSeminar will focus on the process used by the Karmanos Cancer Institute to focus their cytogenomic analyses, highlighting a pilot study to understand the drivers for metastases to the brain from primary lung and breast cancers.

2:45 Sponsored Presentation (Opportunity Available)

3:00 Refreshment Break with Exhibit and Poster Viewing

3:45 Individual Patient Full-Genome Cancer Profiling for Optimized Treatment Strategies 

Raphael Lehrer, Founder and Chief Scientist, GeneKey

Here we describe how to use a combination of multiple full genome technologies to triangulate on key dysregulated mechanisms in a patient's sample. In particular, we focus on a systems biology approach which we combine with statistical algorithms to distinguish data from noise. We describe how this is applied in the clinic with patients and their oncologists and what we have seen/learned to date, including cases where the dysfunction is not mutation based. We further describe how this can be used to accelerate discovery of subtypes of cancer.

4:15 Clinical Genomics in a Breast Cancer Multidisciplinary Tumor Board

Peter J. Tonellato, Ph.D., Director, Laboratory for Personalized Medicine, Center for Biomedical Informatics, Department of Pathology, Beth Israel Deaconess Medical Center and Harvard Medical School

Beth Israel Deaconess Medical Center and Harvard Medical School, Center for Biomedical Informatics have joined together to produce a whole cancer genome analysis software system that produces clinically actionable data and information that is assessed by the BIDMC Breast Cancer Tumor Board. Though not integrated into best practice medicine, the system validation will provide significant information as to the value of such a process in routine breast cancer healthcare.

4:45 Personalized, Precision Lung Cancer Medicine through Integrated Genomic Analysis

Trever Bivona, M.D., Ph.D., Assistant Professor, Medicine/Hematology-Oncology, University of California, San Francisco

We have established a robust and high-throughput platform for the systematic identification of molecular biomarkers of response and resistance to specific targeted therapies in patients with lung cancer. We conduct integrated genomic analysis, through whole genome and transcriptome deep sequencing, of clinical specimens obtained from active patients prior to and during therapy to identify molecular biomarkers of therapeutic response and therapeutic targets. This information is synthesized in a clinical time frame and used to direct the mechanism-based treatment of lung cancer patients. The results and full implications of our approach for improving outcomes for cancer patients will be discussed.

5:15 ICAN (International Cancer Advocacy Network) — Supporting Personalized Cancer Patient Care in and behind the Trenches

Scott M. Kahn, Ph.D., Adjunct Associate Research Scientist, Department of Urology; Member, Herbert Irving Comprehensive Cancer Center, Columbia University; Chairman, Biomarkers Council, International Cancer Advocacy Network (ICAN)

5:45 Welcome Reception with Exhibit and Poster Viewing

6:45 End of Day


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