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FINDING CURES TOGETHER<sup>SM</sup>

30th Anniversary AACR Special Conference Convergence: Artificial Intelligence, Big Data, and Prediction in Cancer

​Program   

Sunday, Oct. 14 

Monday, Oct. 15

Tuesday, Oct. 16

Wednesday, Oct. 17


Sunday, Oct. 14

Welcome
6-6:30 p.m.

Welcome  
Margaret Foti, American Association for Cancer Research, Philadelphia, Pennsylvania

Conference Overview
Phillip A. Sharp, David H. Koch Institute for Integrative Cancer Research at MIT, Cambridge, Massachusetts


Keynote Lectures

6:30-8 p.m.

Detection of cancer with circulating nucleic acids
Richard Klausner, Mindstrong Health, Palo Alto, California

Title to be announced
Aviv Regev, Massachusetts Institute of Technology, Cambridge, Massachusetts


Opening Reception
8-9:30 p.m.


Top of page


Monday, Oct. 15  

Continental Breakfast
7-8 a.m.


Plenary Session 1: Predicting the Genetic/Environmental  Causes of Cancer

8-10 a.m.

The fourth revolution in cancer research: From phenotype to molecular biology to omics to data science
Alan Bernstein, Canadian Institute for Advanced Research (CIFAR), Toronto, ON, Canada

Models of pancreatic cancer risk
Alison P. Klein, Johns Hopkins Sidney Kimmel Comprehensive Cancer Center, Baltimore, Maryland

The challenge of characterizing cancer susceptibility
Stephen J. Chanock, National Cancer Institute, Rockville, Maryland

Title to be announced
Anna Goldenberg, University of Toronto, Toronto, ON, Canada

 
Break
10-10:30 a.m.


Plenary Session 2: Predicting Cancer Phenotype through Images

10:30 a.m.-12:30 p.m.

Title to be announced
Josephine Bunch, National Physical Laboratory, Middlesex, England

Assignment of surgical margins with PARP imaging agents in the oral cavity
Thomas Reiner, Memorial Sloan Kettering Cancer Center, New York, New York

Learning disease progression models from images and text
Regina Barzilay, MIT Computer Science and Artificial Intelligence Laboratory, Cambridge, Massachusetts


Free Time / Lunch on Own

12:30-2:30 p.m.


Plenary Session 3: Predicting Cancer Phenotype through  Histology and Pathology

2:45-4:45 p.m.

Predicting cancer phenotype through histology and pathology
Thomas J. Fuchs, Memorial Sloan Kettering Cancer Center, New York, New York

Machine learning approaches to annotate pathology images with high-dimensional cellular state information
Barbara E. Engelhardt, Princeton University, Princeton, New Jersey

Bringing it all together: AI-powered pathology for immuno-oncology
Andrew H. Beck, PathAI, Cambridge, Massachusetts

Title to be announced
Dana Pe'er, Memorial Sloan Kettering Cancer Center, New York, New York

 
Short Talks from Proffered Papers Session 1 
5-5:30 p.m.


Poster Session A / Reception

5:30-7:30 p.m.


Free Time / Evening on Own

7:30 p.m.-

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Tuesday, Oct. 16 
 
Continental Breakfast
7-8 a.m.
 
Plenary Session 4: Predicting Cancer Response Using Patient-Centric Data Platforms 
8-10 a.m.

Partnering with patients to advance cancer research
Nikhil Wagle, Dana-Farber Cancer Institute, Boston, Massachusetts

Title to be announced
Joe W. Gray, Oregon Health & Science University, Portland, Oregon

Emerging opportunities at the intersection of computational oncology and precision cancer medicine
Eliezer M. Van Allen, Dana-Farber Cancer Institute, Boston, Massachusetts

Title to be announced
Stephen M. Friend, Sage Bionetworks, Seattle, Washington


Break
10-10:30 a.m.

 
Plenary Session 5: Predicting Cancer Response to Precision Therapy 
10:30 a.m.-12:30 p.m.

Heterogeneity and evolution of gliomas
Raul Rabadan, Columbia University Medical Center, New York, New York

Defining a cancer dependency map
William C. Hahn, Dana-Farber Cancer Institute, Boston, Massachusetts

Identification of breast cancer drivers and therapy resistance mechanisms in mouse models
Jos Jonkers, Netherlands Cancer Institute, Amsterdam, Netherlands

Title to be announced
Alice T. Shaw, Massachusetts General Hospital Cancer Center, Boston, Massachusetts

 
Free Time / Lunch on Own
12:30-2:30 p.m.

Special Session: New Funding Opportunities from the NCI Center for Cancer Training  
1:45-2:30 p.m.

Michele McGuirl, Center for Cancer Training, National Cancer Institute, Bethesda, Maryland

A new NCI funding opportunity is expected to be published in late 2018 for early-stage postdocs who wish to pursue careers as independent cancer researchers, and those in data and population sciences are especially encouraged to apply. Mentors and potential applicants (including international students and postdocs) are invited to learn more about this new pilot program and other funding opportunities offered by NCI.


Plenary Session 6: Predicting the Impact of Early Intervention in Cancer  
2:45-4:45 p.m.

RNA-based elucidation of pharmacologically actionable dependencies in human malignancies
Andrea Califano, Columbia University, New York, New York

Making hay of needles: Connecting clinical and physical parameters in the search for early cancer
Imran S. Haque, Freenome, South San Francisco, California

Title to be announced
Brian M. Wolpin, Dana-Farber Cancer Institute, Boston, Massachusetts

Short Talks from Proffered Papers Session 2  
4:45-5:15 p.m.

 
Poster Session B / Reception
5:15-7:15 p.m.

 
Free Time / Evening on Own
7:15 p.m.-

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Wednesday, Oct. 17    

Continental Breakfast
7-8 a.m.
 
Plenary Session 7: Predicting Immune Response to Cancer 
8-10 a.m.

Title to be announced
Elizabeth M. Jaffee, Johns Hopkins Sidney Kimmel Comprehensive Cancer Center, Baltimore, Maryland

Multi-omic, dynamic data clouds for early detection of cancer or cancer recurrence
James R. Heath, Institute of Systems Biology, Seattle, Washington

The predictive value of the pre-existing immune contexture and Immunoscore
Jerome Galon, INSERM UMRS1138, Cordeliers Research Center, Paris, France

Identifying and tracking tumor-specific T-cell clones
Harlan Robins, Adaptive Biotechnologies Corporation, Seattle, Washington


Break

10-10:15 a.m.


Plenary Session 8: Predicting Cancer Status by Metabolic  Changes

10:15-12:15 p.m.

Title to be announced
Nir Yosef, UC Berkeley Center for Computational Biology, Berkeley, California

Metabolic reprogramming in human tumors in vivo
Ralph J. DeBerardinis, UT Southwestern Medical Center, Dallas, Texas

Title to be announced
Matthew G. Vander Heiden, David H. Koch Institute for Integrative Cancer Research at MIT, Cambridge, Massachusetts

Urea cycle dysregulation, emerging pyrimidines mutation bias, and enhanced response to immunotherapy in cancer
Eytan Ruppin, National Cancer Institute, Bethesda, Maryland


Closing Remarks
12:15-12:30 p.m.

Phillip A. Sharp, David H. Koch Institute for Integrative Cancer Research at MIT, Cambridge, Massachusetts

William C. Hahn, Dana-Farber Cancer Institute, Boston, Massachusetts

 
Departure

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