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החוג ללימודי הסביבה

קולוקוויום בביה"ס למדעי המחשב - Dissecting the evolution and state-space of tumors using single cell genomics

Matan Hofree (Broad Institute)

26 בינואר 2020, 11:00 
בניין צ'ק פוינט, חדר 420 
קולוקוויום במדעי המחשב

Abstract:
The evolution of tumors from individual cells with genetic aberrations into a malignant tissue
remains poorly understood. In this talk, I will describe key findings from multiple studies
shedding light on prominent features of tumor formation, derived from analysis of single cell
transcriptional profiles from mouse models and human cancers. In the first study, we examined
the cell states of tumors arising from identical genomic origins in a mouse model of lung cancer,
spanning multiple disease stages. We found that transcriptional diversity was reproducible
across tumors, increased over time, but was not fully explained by genomic copy number
variation. Next, using an optimal transport model to infer likely trajectories across time, we
identified a recurrent, high-plasticity cell state, showing an elevated capacity for tumor
formation. This state emerged early in tumor development and continues to be found through
subsequent stages. Using non-negative matrix factorization we identified sets of genes showing
correlated expression, characteristic of the high-plasticity state, as well as multiple others
corresponding to additional differentiation paths in these tumors. Using these gene-sets we
infer the activity states in transcriptional data from human tumors, which showed a significant
predictive value for survival outcomes. In a separate study, we examined the transcriptional cell
states of the prostate, during castration, and regeneration following the reintroduction of
androgen. Remarkably, we find that the regeneration of this tissue is not dependent on a rare
stem cell population, but rather on proliferation of the majority of luminal prostate cells
persisting after castration. Finally, I will describe recent efforts to understand tumor-
microenvironment interactions in a cohort of colorectal cancer patients. Throughout the talk I
will highlight computational approaches and tools for analysis of single cell data at scale.

Bio:
Matan Hofree is a Postdoctoral Associate at the Broad Institute of MIT and Harvard, a member
of the Regev lab and the Klarman Cell Observatory. He applies and develops computational
analysis techniques for studying cancer and complex genetic disease, with a particular focus on
single cell transcriptomics. Working in close collaborations with clinicians and experimentalists,
he aims to advance our understanding of the roles of transcriptional plasticity and cellular
heterogeneity in the emergence and evolution of tumors. Matan earned his PhD from the
Computer Science department of UC San Diego, working under the supervision of Trey Ideker.
His graduate research focused on developing approaches for improved inference, classification,
and clustering, using prior biological knowledge encoded in gene interaction networks. He
received his B.Sc. in Computer Science and Computational Biology from the Hebrew University
of Jerusalem, in Israel. 

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