Quantifying chromosomal instability from intratumoral karyotype diversity using agent-based modeling and Bayesian inference

Abstract

Chromosomal instability (CIN) — persistent chromosome gain or loss through abnormal karyokinesis — is a hallmark of cancer that drives aneuploidy. Intrinsic chromosome mis-segregation rates, a measure of CIN, can inform prognosis and are a likely biomarker for response to anti-microtubule agents. However, existing methodologies to measure this rate are labor intensive, indirect, and confounded by karyotype selection reducing observable diversity. We developed a framework to simulate and measure CIN, accounting for karyotype selection, and recapitulated karyotype-level clonality in simulated populations. We leveraged approximate Bayesian computation using phylogenetic topology and diversity to infer mis-segregation rates and karyotype selection from single-cell DNA sequencing data. Experimental validation of this approach revealed extensive chromosome mis-segregation rates caused by the chemotherapy paclitaxel (17.5±0.14/division). Extending this approach to clinical samples revealed the inferred rates fell within direct observations of cancer cell lines. This work provides the necessary framework to quantify CIN in human tumors and develop it as a predictive biomarker.

A survey of CIN measures across mechanistic models

“…CtrlM cells had inferred mis-segregation rates at 0.83±0.64 MDD while the Pb, Mp, and Po models had much higher mis-segregation rates of 5.4±0.5, 6.5±1.3, and 11.3±1.8 MDD respectively (Figure 5I). In comparison, the approximated mis-segregation rates of in RPE1 cells is 0.01-0.05 MDD and for U2OS, 0.33-0.46 MDD (36). These rates compare favorably with the number of deviations measured directly from whole chromosome copy number data, particularly when accounting for the partial induction of CIN over 8 hours with the Po model (Figure 5B).…”

“…First, we performed dimensionality reduction, which verified that the biological data falls within the 'summary space' of the simulated data (Figure 5H). Inferring mis-segregation rates (taken as the average of the posterior rate distributions) revealed a wide range across models from 0.3-11.5 MDD (36,48). There was only a 2-fold increase in mis-segregation rate in the Br model of bridging chromosomes: CtrlC and Br showed mis-segregation rates of 0.12±0.07 and 0.28±0.02 MDD respectively.…”

“…As expected, all had statistically elevated CIN over controls and the two methods were closely correlated (Figure 2K). To directly compare the relative levels of CIN imparted by each model, we quantified a standardized measure of CIN, mis-segregations per diploid division (MDD), which we previously described (36). This measure accounts for the relative mis-segregation rates produced by different CIN phenotypes, the relative penetrance of these phenotypes, and the ploidy of the cell.…”

Proliferative advantage of specific aneuploid cells drives evolution of tumor karyotypes

“…While in healthy cells, aneuploidy causes a strong anti-proliferative response as a result of gene dosage imbalances (Santaguida et al, 2015) this response can be overcome in cancer cells, allowing the increased frequency of errors to promote aneuploid karyotype evolution and acceleration of tumor formation (Duijf & Benezra, 2013;van Jaarsveld & Kops, 2016). These ideas have emerged from extensive studies of aneuploidy in different systems including cell lines (Cimini et al, 2001;Thompson & Compton, 2008, 2011a, organoids (Bolhaqueiro et al, 2019;Drost & Clevers, 2018;Narkar et al, 2021), animal models (Bolton et al, 2016;Sheppard et al, 2012;Shoshani et al, 2021;Trakala et al, 2021), as well as theoretically (Araujo et al, 2013;Desper et al, 2005;Elizalde et al, 2018;Gusev et al, 2000Gusev et al, , 2001Laughney et al, 2015;Lynch et al, 2021). Yet, how the interplay between chromosome missegregation, cell proliferation and other processes drives long-term karyotype evolution is poorly understood.…”

“…A study of karyotype evolution that includes the interplay between missegregation and whole genome duplication found that population converges to near triploid state (Laughney et al, 2015), and that heterogeneity is primary influenced by the missegregation rate (Elizalde et al, 2018). Recently, a theoretical model was developed to measure CIN from karyotype diversity within a tumor (Lynch et al, 2022).…”