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Modeling Evolutionary Dynamics
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With the rise of cancer incidence globally, novel technologies and quantitative tools to dissect and understand complexity of cancer dynamics for effective therapeutic options are being explored.
In many ways, cancers mimic the evolutionary process of species, where the heterogeneous population of cells adapt to ecological niches - to thrive and persist. Hence, mathematical models that have been implemented to uncover evolutionary processes are being applied to uncover the evolutionary dynamics of cancers. This is based on the premise that they are governed by the same universal laws, where each cell represents an individual within a heterogeneous and dynamic population. The mathematical models to understand these phenomena are mostly derived from (a) population genetics, which captures the dynamics of genetic variation within the population through use of stochastic and deterministic models in well-mixed and structured populations (b) phylogenetic tree reconstruction methods to infer the evolutionary history of cancer subclones through acquisition of new driver mutations.
In our upcoming mini-series of lectures, Prof. Alison Etheridge from University of Oxford and Prof. Amaury Lambert from Sorbonne Université will describe exciting probabilistic models of evolution that may be highly relevant for understanding cancer evolution and dynamics.
Prof. Lambert’s lecture series will focus on “Evolutionary processes and patterns in biodiversity”. He will begin his lecture series on Oct 9th, by describing how coalescence models can be applied to understand genetic diversity dynamics. On Oct 16th, his second lecture, “The formation of new species”, will apply birth-death processes and coalescent point processes to describe phylogenetic trees. The final lecture of Lambert’s series, held on Oct 23rd and entitled “Coevolving genes and species”, will describe models for recombination and hybridization between different species and genes.
Prof. Etheridge’s lecture series on “Some mathematical models of evolution” will begin on Nov 6th on the topic of “Spatial population models”, modelling the interactions between the forces of evolution including genetic drift and spatial structure of a population. This will be followed by her lecture on Nov 13th on “Expanding populations” where she will apply the (stochastic) Fisher-KPP equation to describe how populations initially expand into uncrowded environments. The series will culminate with a lecture on Nov 20th on “The infinitesimal model and evolutionary rescue” which tries to model scenarios where selection is controlled by the accumulation of many small effects at a very large number of loci.
The links for registering for these lectures can be found here.
The potential of implementing such mathematical models to study cancer evolution is exciting – potentially offering insights for designing next generation cancer therapeutics. Targeting the dynamic interplay between the clonally diverse cancer cells, stromal and immune cells within its microenvironment by implementing both adaptive and sequential therapeutic strategies seems attractive. The advent of emerging technologies that provide single-cell resolution data at molecular (genomic, transcriptomic, epigenetic, metabolomics) and cellular level with intact spatio-temporal structure, as offered by varied imaging technologies will play a crucial in these new developments. In a distant future, one can envision adaptive treatment approaches that can respond to the highly dynamic cellular population within tumors.
⁃Written by Presha Rajbhandari, Postdoctoral Research Scientist in the Department of Biological Sciences, Brent Stockwell lab
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Meet Our Associate Members
In this monthly newsletter, we will regularly feature
the many talented members of our Institute.
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Jellert Gaublomme is an Assistant Professor in the department of Biological Sciences at Columbia University. His lab develops and applies multi-omic technologies to study biomolecular and cellular interactions during development, physiology and pathology. The application areas include immunology, neuroscience and cancer. Jellert is also an associate member of the Herbert and Florence Irving Institute for Cancer Dynamics, where he collaborates with Elham Azizi and Brent Stockwell on probabilistic modeling of intercellular interactions that drive ferroptosis susceptibility of therapy-resistant cancer cells.
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Itsik Pe’er is an associate professor in the Department of Computer Science at Columbia University. His laboratory develops and applies computational methods for the analysis of high-throughput data in germline human genetics. Specifically, he has a strong interest in isolated populations such as Pacific Islanders and Ashkenazi Jews. Itsik is also an associate member of the Herbert and Florence Irving Institute for Cancer Dynamics, where his computational expertise has been invaluable in assessing applicants for research positions.
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Announcement from the Pe’er lab:
Welcome new students Philippe Chlenski and Yining Liu (with Andrew Blumberg)
Congratulations to Jie Yuan for publishing his paper titled "Leveraging correlations between variants in polygenic risk scores to detect heterogeneity in GWAS cohorts" in PLoS Genetics
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