HiTS Seminar: Christina Leslie, 10:00 am, Thursday, May 2, 2019

 

Christine Leslie, Ph.D.

Associate Member, Computational Biology Program
Sloan Kettering Institute

 

Decoding Epigenetic States of Immune and Cancer Cells

 
Dysregulated epigenetic programs are a feature of many cancers, and the diverse differentiation states of immune cells as well as their dysfunctional states in tumors are in part epigenetically encoded.  We will present recent analysis work and computational methodologies from our lab to decode epigenetic programs from genome-wide data sets. In a recent collaborative work, we characterized chromatin states governing CD8 T cell dysfunction in cancer and reported that tumor-specific T cells differentiate to dysfunction through two discrete chromatin states: an initial plastic state that can be functionally rescued (i.e. through immunotherapy) and a later fixed state that is resistant to therapeutic reprogramming.  We now follow up on this work by presenting a computational framework to decipher transcriptional programs governing chromatin accessibility and gene expression in normal and dysfunctional T cell responses through a large-scale analysis of published data from mouse tumor and chronic viral infection models.  This modeling shows that in all these systems, T cells commit to becoming dysfunctional early after an immune challenge, rather than first mounting and then losing an effector response.  Through scRNA-seq analysis, we characterize the phenotypic diversity of this common trajectory from plastic to fixed dysfunction.  We will also present a recent collaboration with the Sawyers lab on FOXA1 mutants in prostate cancer, showing that somatic alterations in this pioneer transcription factor lead to altered differentiation programs, through analysis of ATAC-seq in mouse prostate organoid systems.  Finally, we will describe a novel machine learning approach called BindSpace to leverage massive in vitro TF binding data from SELEX-seq experiments through a joint embedding of DNA k-mers and TF labels, leading to improved prediction of TF binding.
 

10:00 am – 11:00 am
Thursday, May 2, 2019

Harvard Medical School
210 Longwood Avenue
Goldenson Bldg, Room 122
Boston, MA 02115

Hosted by Artem Sokolov, Ph.D.

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