The Landscape of Receptor-Mediated Precision Cancer Combination Therapy: A Single-Cell Perspective

Abstract

Combining the paradigms of personalized medicine, modular treatment strategies, and single-cell data sets, we formulate a two-layered combinatorial optimization problem that models a modular approach to personalized cancer treatment. We seek to make principled estimates of quantities such as: How many different treatments are needed to kill all cells in a tumor? If one can kill all cells in a tumor, what fraction of normal cells nearby will also get killed as a side effect of the combination therapy?In this subsection, we review two types of related work in the area of combinatorial optimization. The first type of related work is applications of a problem called "hitting set" in bioinformatics. The second type of related work is other multi-layered problems in combinatorial optimization (defined and described below).