University of Cambridge > > Seminars on Quantitative Biology @ CRUK Cambridge Institute  > Engineering model-based systems to monitor and steer subclonal dynamics

Engineering model-based systems to monitor and steer subclonal dynamics

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If you have a question about this talk, please contact Florian Markowetz.

Primary tumors as well as cancer cell lines have been shown to exhibit extensive genetic and transcriptional heterogeneity, with multiple subclones co-existing in the same cancer population. Even after decades of in-vitro growth, established cell cultures continue to evolve.

The heterogeneity of cancer cell lines over space and time crystallizes into three unmet needs: i) cell culture protocols that offer a high temporal resolution on in-vitro growth dynamics; ii) close monitoring of the temporal separation between genotypic and phenotypic measurements and iii) reconciling the cost-prohibitive nature of high-throughput multi-omic measurements with ceaseless changes in subclonal composition.

To fill these needs, we propose to engineer how in-vitro and in-silico experiments interact into a modular software solution called CLONEID . CLONEID’s first module records the pedigree of lineages grown in a lab and uses computer vision to monitor phenotypic changes, such as variable growth rates. The second module links subclonal multi-omics profiles from different high throughput assays to each other and to the phenotypes from the first module.

We demonstrate feasibility of monitoring phenotypic transitions in cancer cell lines with CLONEID at high temporal resolution, without any specialized equipment. Using this data in conjunction with single cell sequencing of the same cell lines, we prioritize subclone-specific expression signatures of growth. Our framework represents an early step towards more complex mathematical models of carcinogenesis, that do not have to rely on simplifying assumptions that individual driver mutations have equal fitness effects and that individual subclones have a fixed growth rate.

Short bio:

My Ph.D. in Bioinformatics was under the supervision of Hans Werner Mewes from the Technical University in Munich and Claudia Petritsch from the University of California, San Francisco. Together we developed one of the first algorithms that deconvolutes a tumor’s sequencing data into clones that coexist in the tumor biopsy. As a postdoctoral fellow, together with Hanlee Ji and Carlo Maley, I quantified intra-tumor heterogeneity in >1000 primary tumors to find that coexistence of multiple clones in the same tumor is indeed the norm. As an Instructor at Stanford in Prof. Ji’s lab, I integrated bulk- and single-cell sequencing approaches to zoom into different perspectives of intra-tumor heterogeneity. The newly gained resolution on coexisting clones and their microenvironment puts us in the yet best position to control and steer subclonal evolution.


This talk is part of the Seminars on Quantitative Biology @ CRUK Cambridge Institute series.

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