Tissue level insights from cellular measurements. Matan Hofree (Weizmann)

Department of Computer Science – Bar-Ilan University
Computer Science Colloquium
Monday, April 25, 2022
12:00 P.M.
Dr. Matan Hofree
Weizmann Institute

Will lecture on:
Tissue level insights from cellular measurements
Identifying multi-cellular hubs by co-variation analysis of single-cell expression Therapy response varies considerably among cancer patients and depends on tumor intrinsic factors and interactions with the tumor microenvironment and the immune system. In colorectal cancer (CRC), response to immune therapy varies between patients with mismatch repair-deficient (MMRd) and mismatch-repair proficient tumors (MMRp). Most MMRd tumors show immune cell activity and a favorable response to immune therapy. To understand the difference between these cancer subtypes, we transcriptionally profiled tumor and adjacent normal tissue from MMRp and MMRd patients by single-cell RNAseq. Using unsupervised analysis, we characterized the cellular composition of these tumors, identifying 88 cell subsets from 7 distinct cell lineages and an associated compendium of cell-type-specific gene expression programs. To discover multi-cellular interactions between cancer and immune cells, we identified expression programs with elevated co-variation across patient tumors. Using graph clustering uncovered tumor-type specific hubs of significant co-variation between cell types. We localized two hubs of particular interest involving the co-activation of malignant and immune-specific programs using spatial profiling. This work demonstrates the potential of co-variation analysis to reveal logic underlying multi-cellular interactions in cancer and disease. Throughout the talk, I will highlight computational approaches and data analysis ideas applicable to single-cell and other high-dimensional measurement types.

Short bio:
Matan Hofree received his B.Sc. in Computer Science and Computational Biology from the Hebrew University of Jerusalem. He earned his Ph.D. in Computer Science from UC San Diego, working under Prof. Trey Ideker, where he developed approaches for improved inference, classification, and clustering, using prior biological knowledge encoded in gene interaction networks. He was a Postdoctoral Associate at the Broad Institute of MIT and Harvard, a member of the Regev lab and the Klarman Cell Observatory. Dr. Hofree is currently a visiting scientist at the Department of Biological Regulation of the Weizmann Institute. He develops computational analysis techniques for studying cancer and complex genetic disease, using algorithms and ideas from machine learning and graph theory. Matan focuses on advancing our understanding of the interplay between genetic mutations, transcriptional changes, and cell-cell interactions and how these drive the emergence and evolution of tumors.

Building 216 Room 201