A Combination Approach of Pseudotime Analysis And Mathematical Modeling For Understanding The Drug-Resistant Mechanisms

Abstract

Cancer cells acquire drug resistance through the following nonresistant, pre-resistant, and resistant stages. Although the molecular mechanism of drug resistance is well investigated, the process of drug resistance acquisition remains largely unknown. Here we elucidate the molecular mechanisms underlying the process of drug resistance acquisition by sequential analysis of gene expression patterns in tamoxifen-treated breast cancer cells. Single-cell RNA-sequencing indicates that tamoxifen-resistant cells can be subgrouped into two, one showing altered gene expression related to metabolic regulation. The other showed high expression levels of adhesion-related molecules and histone-modifying enzymes. Pseudotime analysis showed a cell transition trajectory to the two resistant subgroups that stem from a shared pre-resistant state. An ordinary differential equation model based on the trajectory fitted well with the experimental results of cell growth. Based on the established model, it was predicted and experimentally validated that inhibition of transition to both resistant subtypes would prevent the appearance of tamoxifen resistance.