Convergence 2.0 Project Summaries

The following is a list of the teams and project summaries chosen to participate in Convergence 2.0 by the Convergence 2.0 Selection Committee and SU2C Scientific Advisory Committee :

Computational deconstruction of neoantigen-TCR degeneracy for cancer immunotherapy

Additional Support: Lustgarten Foundation; SITC

Team Leaders: Benjamin Greenbaum, PhD, at the Icahn School of Medicine at Mount Sinai Hospital; Vinod Balachandran, MD, Memorial Sloan Kettering Cancer Center

Team Members: Marta Łuksza, PhD, Icahn School of Medicine at Mount Sinai; Eileen M. O'Reilly, MD, David M. Rubenstein Center for Pancreatic Cancer Research; Jedd Wolchok, MD, PhD, Memorial Sloan Kettering Cancer Center

Collaborators: Nina Bhardwaj, MD, PhD, Icahn School of Medicine at Mount Sinai; Curtis Callan, PhD, Princeton University; Timothy Chan, MD, PhD, Memorial Sloan Kettering Cancer Center; Simona Cocco, PhD, Ecole Normale Supérieure; Jeffrey Drebin, MD, PhD, Memorial Sloan Kettering Cancer Center; Anthony Gill, MD, Professor of Surgical Pathology, University of Sydney; Christine Iacobuzio-Donahue, MD, PhD, Memorial Sloan Kettering Cancer Center; Dmitry Krotov, PhD, Member, Institute for Advanced Study; Taha Merghoub, PhD, Memorial Sloan Kettering Cancer Center; Rémi Monasson, PhD, Centre National de la Recherche Scientifique; Thierry Mora, Ecole Normale Supérieure; Aleksandra Walczak, PhD, Ecole Normale Supérieure

Project Summary: The team will build on the work started under a Convergence 1.0 grant but further explore the underpinnings that constitute pancreatic survivorship. By looking at the few individuals who survive pancreatic cancer for long periods of time, the team identified an initial set of high-quality neoantigens, or protein tags, on cancer cells that the immune system recognizes.  This project will continue the work to understand what makes a high-quality neoantigen and how the microbiome influences how the immune system recognizes it, with the goal of developing a method for creating vaccines to treat pancreatic cancers.  This research will have a significant impact on understanding neoantigen-T cell immunobiology and could improve the treatment prospects of pancreatic cancer patients.

Single-Cell Functional Multi-Omics to Characterize and Monitor CAR T Therapy

Additional Support: SITC

Team Leader: Rong Fan, PhD, Yale University;

Team Members: Stephanie Halene, MD, PhD, Yale School of Medicine and Yale University; Carl H. June, MD, University of Pennsylvania Perelman School of Medicine; Pablo G. Cámara, PhD, University of Pennsylvania Perelman School of Medicine; J. Joseph (“Jos”) Melenhorst, University of Pennsylvania Perelman School of Medicine

Project Summary: Immunotoxicity and autoimmune-like response is a significant problem hindering widespread use of cancer immunotherapies. Major players in the immune response are cytokines, which are substances secreted by some immune cells to affect other cells in response to a signal, e.g., recognition of a foreign body. To understand this response, the full spectrum of cytokine functions in a pre-infusion setting will be assessed and matched with patient responses to treatment with the chimeric antigen receptor (CAR) T therapy. Afterward, the function of the infused CAR T cells will be assessed to determine the mechanisms of efficacy and/or immune toxicity. The team also proposes identifying molecular characteristics underlying therapeutic efficacy and toxicity of CAR T therapy, and biomarker discovery by using computational models and machine learning that look at the data. If successful, this will create a “tool” that clinicians can use to mitigate patient risk associated with CAR T therapies while improving the chances of therapeutic success.

Integrating Experimental and Computational Pipelines to Develop Biomarkers of Tumor Cell Resistance to NK Cells

Team Leader: Constantine Mitsiades, MD, PhD, Dana-Farber Cancer Institute

Team Members: Michal Sheffer, PhD, Dana-Farber Cancer Institute; Ricardo de Matos Simoes, PhD, Dana-Farber Cancer Institute; Aedin Culhane, PhD, Dana-Farber Cancer Institute; Todd Golub, MD, Broad Institute of MIT and Harvard; Aviad Tsherniak, MSc, Broad Institute of MIT and Harvard; Christopher Mader, PhD; Broad Institute of MIT and Harvard; Jennifer Roth, MSc, MBA, Broad Institute of MIT and Harvard

Collaborators: Jacob Laubach, MD, Dana-Farber Cancer Institute; Paul G. Richardson, MD, Dana-Farber Cancer Institute; Rizwan Romee, MD, Washington University School of Medicine in St. Louis; Jerome Ritz, MD, Dana-Farber Cancer Institute; Lotte Wieten, PhD, Maastricht University Medical Center, Netherlands; Richard Groen, PhD, VU Medical Center, Amsterdam, Netherlands

Project Summary: Natural killer (NK) cells, white blood cells that play a role in viral response, have potent anti-tumor cell killing properties. Moreover, NK cells are not inhibited by many of the strategies cancer cells use to evade the immune system. This team hypothesizes that the genetic make-up of a tumor may serve as a basis to target its destruction by NK cells. To identify biomarkers that are responsible for tumor cell sensitivity or resistance to NK cells, the team will use computational approaches. The team members will also explore novel interaction patterns based on NK responses by using tools such as CRISPR screens. Finally, these biomarkers will be validated on different experimental platforms such as patient-derived organoids and high-throughput systems to quantify tumor cell responses to immune effector cells. Results from this research could have an impact on models used to study a wide range of cancers.

Correlating Immunological Health to Cancer Susceptibility

Additional Support: SITC

Team Leader: Mark Davis, PhD, Stanford University

Team Members: Stephen Quake, PhD, Stanford University; Thomas Montine, MD, PhD, Stanford University; Kari Nadeau, MD, PhD, Stanford University; David Furman, PhD, University of Buenos Aires, Argentina

Project Summary: A preliminary analysis of over 450 adults showed that the immune response to influenza vaccine may be correlated with cancer susceptibility. In a small subset of elderly subjects who received the influenza vaccine, subjects with less robust immune response were more likely to develop and succumb to cancer. This team will correlate the varying immune cell (T- and B-cell populations) repertoires in individual patients with cancer susceptibility, comparing the results to a separate cohort of patients who are immune deficient. Even partial success could lead to testable signatures for cancer prediction.

Connecting Immune Health and Tumor Biology in Gynecologic Cancers

Additional Support: SITC

Team Leader: John Wherry, PhD, University of Pennsylvania

Team Members: Claire Friedman, MD, Memorial Sloan Kettering Cancer Center; Robert Burger, MD, FACOG, FACS, The Hospital of the University of Pennsylvania; Daniel Powell, PhD, University of Pennsylvania;  Shelley Berger, PhD, Perelman School of Medicine University of Pennsylvania; Erica Carpenter, MBA, PhD, Perelman School of Medicine University of Pennsylvania; Dana Pe’er, PhD, Memorial Sloan Kettering Cancer Center; Dmitriy Zamarin, MD, PhD, Memorial Sloan Kettering Cancer Center; Travis Hollman, MD, PhD, Memorial Sloan Kettering Cancer Center

Collaborators: Benjamin Greenbaum, PhD, Icahn School of Medicine at Mount Sinai; David Ting, MD, Massachusetts General Hospital/Harvard Medical School; Ernest Fraenkel, PhD, Massachusetts Institute of Technology

Project Summary: Mismatch repair (MMR)-deficiency, the inability to repair base pairing within the DNA helix, can give rise to a weakened DNA structure, which leads to the accumulation of mutations. The response to immune checkpoint inhibitors has been varied in gynecologic cancers, possibly due to the number of mutations carried by each tumor cell (mutational burden). The team hypothesizes that the tumors with a high mutational burden fail to respond to checkpoint inhibition because of an immune dysfunction that is based on the mechanism for the MMR deficiency. The team plans to initiate two clinical trials that will test whether a) tumor-intrinsic factors affect the response to checkpoint inhibition; b) baseline immune function and quality affects response to checkpoint inhibition; and c) on-treatment blood markers may reflect the tumor-immune interaction. Understanding the mechanism that leads to this phenomenon has the potential to dramatically affect those patients who do not respond to current treatments.

Responders and Non-responders to Endometrial Cancers with Mismatch Repair

Team Leader: Alessandro Santin, MD, Yale University School of Medicine

Team Members: Ludmil Alexandrov, PhD, University of California San Diego; Akiko Iwasaki, PhD, Yale University School of Medicine; and Stefania Bellone, PhD, Yale University

Collaborator: Richard Lifton, MD, PhD, President of Rockefeller University

Project Summary: Researchers do not know why only about one-half of all patients with mismatch repair deficient, MSI-high(h) metastatic/recurrent tumors respond to anti-PD1 treatment. The team will develop and validate a novel computational method to assess DNA damage and tumor mutational burden using next-generation sequencing data. Once validated, the approach will be applied to an ongoing trial for patients with endometrial cancer treated with Pembrolizumab. The team hopes to be able to predict the patients who will have side effects to checkpoint therapies, predict antigens from T cell receptor sequences, and determine neoantigens that are expressed by tumors that are recognized by the immune system in an HLA-dependent fashion. Identification of the patients who will have side effects will allow for modification of treatment to mitigate the adverse effects.

Using Artificial Intelligence to predict molecular pathways and clinical outcomes

Additional Support: SITC

Team Leader: Ernest Fraenkel, PhD, Massachusetts Institute of Technology

Team Member: Regina Barzilay, PhD, Massachusetts Institute of Technology

Collaborators: John Wherry, PhD, University of Pennsylvania; Claire Friedman, MD, Memorial Sloan Kettering Cancer Center; Constantine Mitsiades, MD, PhD, Dana-Farber Cancer Institute; Todd Golub, MD, Broad Institute of MIT and Harvard; Jerome Ritz, MD, Dana-Farber Cancer Institute

Project Summary: Recent successes in cancer immunotherapy have raised high hopes that these approaches can be expanded to more cancer types and to more patients. However, there are many unmet challenges ahead that will require dramatically new approaches. For example, determining which patients are most likely to benefit from a particular immunotherapy may require integrating diverse types of data (such as lab values) or observational data that are captured in the text of an electronic medical record. As there are no established methods for such complex challenges, this team will develop innovative solutions based on approaches integrating deep, multi-omic data, machine learning, and natural language processing.