Computational Analysis of Treatment Resistant Cancer Cells

Abstract

ABSTRACT Introduction: Prostate cancer (PC), which is a disease driven by the activity of the androgen receptor (AR), is the most commonly diagnosed malignancy and despite advances in diagnostic and treatment strategies, PC is the second most common cause of cancer mortality in men (Bray et al., 2018). Taxane-based chemotherapy is the only chemotherapy that prolongs survival in metastatic PC patients (Petrylak et al., 2004; Tannock et al., 2004). At the cellular level, taxanes bind to and stabilize microtubules (MTs) inhibiting all MT-dependent intracellular pathways. MTs are highly dynamic polymers that stochastically switch between phases of growth, shrinkage, and pause (Jordan and Wilson, 2004). Altered MT dynamics endow cancer cells with both survival and migratory advantages (Mitchison, 2012). Taxanes inhibit MT dynamics and alter the spatial organization of the MT network, thereby inhibiting intracellular trafficking of molecular cargo critical for tumor survival. In PC specifically, taxanes inhibit transcriptional activity downstream of MT stabilization (Thadani-Mulero et al., 2012) and AR nuclear accumulation (Darshan et al., 2011; Zhu et al., 2010). Methods: Different tubulin inhibitors, even from within the same structural class as the taxanes, affect distinct parameters of MT dynamics (Jordan and Wilson, 2004), yet the selection of taxane for chemotherapy is not based on the particular patterns of dynamic behavior of the MT cytoskeleton in individual patients. We envisage that systematic characterization using quantitative analysis of MT dynamics in PC patient cells expressing clinically relevant protein isoforms (Matov, 2024c; Thoma et al., 2010), before and after treatment with each of the taxanes, will allow us to identify criteria for the selection of the most suitable drug combination at the onset of treatment. Results: We link MT dynamics in the presence of AR variants and sensitivity/resistance to taxanes and connect fundamental research with clinically relevant concepts to elucidate cellular mechanisms of  clinical response to taxanes and, thus, advance the customization of therapy.