Abstract

Identification of protein biomarkers for cancer diagnosis and prognosis remains a critical unmet clinical need. A major reason is that the dynamic relationship between proliferating and necrotic cell populations during vascularized tumor growth, and the associated extra- and intra-cellular protein outflux from these populations into blood circulation remains poorly understood. Complementary to experimental efforts, mathematical approaches have been employed to effectively simulate the kinetics of detectable surface proteins (e.g., CA-125) shed into the bloodstream. However, existing models can be difficult to tune and may be unable to capture the dynamics of non-extracellular proteins, such as those shed from necrotic and apoptosing cells. The models may also fail to account for intra-tumoral spatial and microenvironmental heterogeneity. We present a new multi-compartment model to simulate heterogeneously vascularized growing tumors and the corresponding protein outflux. Model parameters can be tuned from histology data, including relative vascular volume, mean vessel diameter, and distance from vasculature to necrotic tissue. The model enables evaluating the difference in shedding rates between extra- and non-extracellular proteins from viable and necrosing cells as a function of heterogeneous vascularization. Simulation results indicate that under certain conditions it is possible for non-extracellular proteins to have superior outflux relative to extracellular proteins. This work contributes towards the goal of cancer biomarker identification by enabling simulation of protein shedding kinetics based on tumor tissue-specific characteristics. Ultimately, we anticipate that models like the one introduced herein will enable examining origins and circulating dynamics of candidate biomarkers, thus facilitating marker selection for validation studies.

Highlights

  • Identification of protein biomarkers for cancer diagnosis and prognosis remains a critical unmet clinical need

  • A major reason is that the relationship between protein abundance in tumor tissue and in blood circulation remains poorly characterized

  • It has proven difficult to link the cell-scale events to the dynamically evolving tissue-scale conditions

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Summary

Introduction

Identification of protein biomarkers for cancer diagnosis and prognosis remains a critical unmet clinical need. Building upon the work of Gambhir and ­coworkers[8], we present a new model that links the levels of protein shedding into circulation to the heterogeneous tumor spatial vascularization and the corresponding proliferating and necrosing cell populations. This is achieved by discretizing tumor tissue into dynamically evolving compartments based on cellular distance from v­ asculature[17], effectively bridging from the cellular to the tissue scale, and enabling prediction of system-level effects from cellular-scale events. By enabling an explicit quantification of necrosis, it becomes tractable to model the shedding of the tens of thousands of non-extracellular proteins

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