The 2014 Phillip A. Sharp Awards for Innovation in Collaboration
The Intersection of Epigenetic and Immune Checkpoint Therapy
Stephen B. Baylin, MD (SU2C Epigenetics Dream Team), Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University
James P. Allison, PhD (SU2C-CRI Immunology Dream Team), The University of Texas MD Anderson Cancer Center
Grant Term: July 2014 – June 2015
This project was focused on combining epigenetic therapy with immune checkpoint inhibition in cancer. Immune checkpoint blockade with antibodies against CTLA4 and PD1/PDL1 can produce durable responses in advanced cancers. Epigenetic mechanisms (mechanisms that modify the DNA to activate or inactivate genes) can affect the response of the immune system to cancer. Previous studies indicated that epigenetic therapy may help patients with advanced non-small cell lung cancer (NSCLC) become more responsive to anti-PD1/PDL1 therapy.
The team has characterized a mechanism through which treatment with epigenetic drugs can make patients more responsive to immune checkpoint therapy. This work has paved the way for development of clinical trials testing the combination of epigenetic drugs and immunotherapy. Two trials are currently being supported by SU2C Catalyst® grants.
cBioPortal for Stand Up To Cancer
David B. Solit, MD (SU2C-MRA Melanoma Dream Team), Memorial Sloan Kettering Cancer Center
Nikolaus Schultz, PhD (SU2C-PCF Prostate Cancer Dream Team), Memorial Sloan Kettering Cancer Center
Grant Term: May 2014 – June 2017
cBioportal for Cancer Genomics, a web-based platform for the analysis and visualization of complex cancer genomic data, has become the method of choice for biologists and clinicians without bioinformatics expertise.
The team released cBioPortal under an open source software license during the funding period of this award, which has made it easier for others to use the software and develop new features. As a result, the cBioPortal software is used at multiple institutions and biotech/pharma companies around the world. As part of this process, the team further simplified the deposition of data into cBioPortal for outside groups.
Analysis of High-dimension Single-cell Data from Cancer Immunotherapy Clinical Trials
Dana Pe'er, PhD (SU2C IRG Recipient), Columbia University
Padmanee Sharma, MD, PhD (SU2C-CRI Immunology Dream Team), The University of Texas MD Anderson Cancer Center
Grant Term: May 2014 – April 2016
T cells, the antitumor effectors in cancer immunotherapy, can be classified into diverse functional subtypes. T cells also produce multiple proteins that need to be simultaneously evaluated to assess the T cells' antitumor activity. Massive amounts of data have been collected on single T cells, and on their secreted proteins. This Sharp Award has been focused on developing powerful computational methods to analyze patient data collected throughout the course of immunotherapy, on characterizing the cells that are affected by immunotherapy, and on connecting the observations to clinical responses.
The Pe'er lab has previously developed three software tools for the analysis of single cell data. The Sharp awardees used these and similar tools to interpret data generated by the SU2C-CRI Immunology Dream Team.
The team observed that 15 different kinds of T cells were found in tumor samples. The most frequently occurring type of T cells had PD-1 and CTLA-4 on their surface. This finding strongly suggests that personalized immunotherapy combination therapies may be needed.
Immune cells from two metastatic melanoma patients who responded, and two patients who did not respond, to anti-PD-1 treatment were studied. The team identified a specific population of immune cells that became more abundant in patients who responded to the immunotherapy.