The ecology of human papillomavirus-induced epithelial lesions and the role of somatic evolution in their progression

Abstract

Background: Human papillomavirus (HPV) infection frequently induces hyperproliferation of epithelial cells, leading to both benign (warts) and malignant tumors (cervical cancer). We seek to understand how HPV may achieve these changes by modulating cellular population dynamics. Furthermore, HPV-induced lesion progression is generally understood as a series of molecular changes. As a complement to this approach, we investigate the role of phenotypic changes produced by natural selection during lesion progression.

Methods: We develop and numerically analyze spatially and evolutionarily explicit mathematical models of HPV-induced epithelial lesions.

Results: Infection of basal cells is a requirement for persistent infection. Increasing the maximum tissue density at which HPV-infected cells can divide and decreasing infected cell migration rate leads to large increases in the number of HPV-infected cells, and consequently, virions shed from the skin surface per day. Evolution by natural selection in an autonomous population of cells leads to tissue changes that are qualitatively similar to those observed during lesion progression.

Conclusions: HPV modulates cell population dynamics, which can be characterized by specific ecological parameters. As an unintended consequence, this ecological strategy of the virus may be successfully co-opted by autonomous host cells and play a role in lesion progression.

Keywords: human papillomavirus; partial differential equation model; somatic evolution.

Figure 1.

Dynamics of infected cells and virion flux in human papillomavirus (HPV)–induced lesions. The left and right panels show the dynamics when basal cells and suprabasal cells are initially infected, respectively.

Figure 2.

The distribution and density of human papillomavirus (HPV)–infected cells and virions in a steady-state 3-dimensional lesion.

Figure 3.

The effects of the model's ecological parameters on virion flux at the skin surface. The top panel shows the effect of the interaction of cell carrying capacity (K_h) and intrinsic growth rate (r_h) on virion flux. The bottom panel shows the effect of the interaction of cell carrying capacity (K_h) and cell migration rate (α_h) on virion flux. Each line is associated with a value of infected cell carrying capacity. These values are given in units of infected cells/mm³.

Figure 4.

Population dynamics of autonomous evolving cells. The top panel shows evolving cells that migrate. The bottom panel shows evolving cells, which have ceased to migrate. The densities of cells shown are integrated over the x and y spatial dimensions.

Figure 5.

Dynamics of human papillomavirus (HPV)–infected cell and virion density as the tumor cells evolve. This is the same simulation as that shown for the evolving cells, which do not migrate in the bottom panel of Figure 4. The top panel shows the dynamics of all HPV-infected cells. The bottom panel shows the virion dynamics. The densities shown are integrated over the x and y spatial dimensions.