Using Genetic Barcoding to Uncover the Evolutionary Dynamics of Drug Resistance Emergence in Colorectal Cancer.
Session type: Poster / e-Poster / Silent Theatre session
Understanding the evolutionary dynamics of cancer cells during drug treatment is crucial to overcome the evolution of drug resistance. This study aimed to monitor the population dynamics of human colorectal cancer (CRC) cell lines in vitro in the presence and absence of clinically-relevant drugs, providing valuable insight into how tumours may grow and respond to chemotherapy treatment.
We adopted a lentivirus genetic barcoding system to track many thousands of individual clonal lineages simultaneously in CRC cells. To determine if longitudinal measurements of clonal dynamics provide an accurate readout of cell turnover, we simulated the experimental evolution of our barcoded populations. We used next generation sequencing to track the relative abundance of specific lineages, allowing us to make inferences about i) cell turnover, ii) the frequency of mutations and iii) the effect of mutations on cell fitness. By observing how these dynamics differ in two different CRC cell lines - characterised by either chromosomal (SW620) or microsatellite (HCT116) instability - we can compare how these two classes of genomic aberration differ in their evolutionary trajectories towards resistance.
Preliminary stochastic birth-death simulations confirmed that by simply observing the distribution of barcodes following a period of growth, we can infer the population’s birth and death rates, confirming that sampling of cells will permit fitness assays that quantify the cost of resistance. Sequencing of barcode tags revealed the relative abundance and clonal complexity of cell line lineages in the presence or absence of drug.
We use a modified virus to uniquely tag CRC cells, tracking their fate as they are subjected to chemotherapy in vitro. Our results will help inform whether the timings of treatment can be used to control the expansion of drug resistant subclones, and if the molecular features of CRC influence the efficacy of this strategy.