Cell types or cell states? An investigation of adrenergic and mesenchymal cell phenotypes in neuroblastoma

Abstract

Neuroblastoma exhibits two cellular phenotypes: therapy-sensitive adrenergic (ADRN) and therapy-resistant mesenchymal (MES). To understand treatment response, it is important to elucidate how these phenotypes impact the dynamics of cancer cell populations and whether they represent distinct cell types or dynamic cell states. Here, we use an integrated experimental and mathematical modeling approach. We experimentally measure the fractions of ADRN and MES phenotypes under baseline (untreated) conditions and under repeated treatment cycles. We develop evolutionary game theoretic models predicting how the populations would respond if ADRN and MES phenotypes (1) are distinct cell types or (2) represent dynamic cell states and fit these models to the experimental data. We find that, although cells may undergo an ADRN to MES phenotypic switch under treatment, the best-fit model sees ADRN and MES as distinct cell types. Differential proliferation and survival of these two cell types, and not cell-state switching, drive therapeutic response.

Keywords: Biological sciences; Neuroscience.

Graphical abstract

Figure 1

The SK-N-BE(2) cell line is dominated by CD44^low cells (A) Schematic image of the experimental setup. (B) Percentages of live CD44^high and CD44^low SK-N-BE(2) cells as determined by flow cytometry for two independent biological repeats. (C) Representative dot plots illustrating SK-N-BE(2) cells 48, 72, and 96 h post seeding. Q1 and Q2 represent dead cells remaining after washing, Q3 CD44^high cells and Q4 CD44^low cells.

Figure 2

Repeated treatment with cisplatin affects CD44 expression of SK-N-BE(2) cells (A) Schematic image of the experimental setup. (B) Percentages of live CD44^high and CD44^low SK-N-BE(2) cells as determined by flow cytometry for two independent biological repeats. (C) Representative dot plots illustrating SK-N-BE(2) cells at treatment start (day 1), after 72 h of treatment (day 4), after 7 days of treatment holiday (day 11), and after a second round of 72 h of treatment (day 14). Q1 and Q2 represent dead cells remaining after washing, Q3 CD44^high cells and Q4 CD44^low cells.

Figure 3

Fit of baseline model to untreated conditions Blue (orange) circles and crosses denote ADRN (MES) frequency measures from the two experimental replicates. Blue and orange lines represent the ADRN and MES model fits, respectively. (A) Fit of baseline model in untreated control. (B) Fit of baseline model in untreated control with state transitions. In accordance with data from Figures 1B and 1C, the ADRN cells have an advantage over the MES cells under baseline conditions.

Figure 4

Fit of cell type model to repeated therapy cycles Blue (orange) circles and crosses denote ADRN (MES) frequency measures from the two experimental replicates. Blue and orange lines represent the ADRN and MES model fits, respectively. Regions shaded in gray denote periods of on therapy, and regions in white are periods off therapy. The model fits the data well and captures key qualitative trends: MES cells increase in frequency during periods of therapy and decrease in frequency during periods of therapy release.

Figure 5

Fits of cell state model to repeated therapy cycles for a range of facultative transition parameter values Cell state transitions, if they occur at all, are likely negligible and do not contribute meaningfully to cell frequency dynamics under treatment. Forcing higher inter-conversion rates leads to poorer model fits.