Nonlinear mixed effects dose response modeling in high throughput drug screens: application to melanoma cell line analysis

Abstract

Cancer cell lines are often used in high throughput drug screens (HTS) to explore the relationship between cell line characteristics and responsiveness to different therapies. Many current analysis methods infer relationships by focusing on one aspect of cell line drug-specific dose-response curves (DRCs), the concentration causing 50% inhibition of a phenotypic endpoint (IC50). Such methods may overlook DRC features and do not simultaneously leverage information about drug response patterns across cell lines, potentially increasing false positive and negative rates in drug response associations. We consider the application of two methods, each rooted in nonlinear mixed effects (NLME) models, that test the relationship relationships between estimated cell line DRCs and factors that might mitigate response. Both methods leverage estimation and testing techniques that consider the simultaneous analysis of different cell lines to draw inferences about any one cell line. One of the methods is designed to provide an omnibus test of the differences between cell line DRCs that is not focused on any one aspect of the DRC (such as the IC50 value). We simulated different settings and compared the different methods on the simulated data. We also compared the proposed methods against traditional IC50-based methods using 40 melanoma cell lines whose transcriptomes, proteomes, and, importantly, BRAF and related mutation profiles were available. Ultimately, we find that the NLME-based methods are more robust, powerful and, for the omnibus test, more flexible, than traditional methods. Their application to the melanoma cell lines reveals insights into factors that may be clinically useful.

Chemogenomic screening Identifies the Hsp70 Co-chaperone HDJ2 as a Hub for Anticancer Drug Resistance

“…Thus, combination anticancer therapies have been used clinically for over 50 years to improve the responses achieved by monotherapies alone. Cancer cell line-based models for these combination therapies are easy and inexpensive to perform using high-throughput drug screening protocols (HTS) to identify the most effective drug combination [25, 26]. HTS helps to explore the relation between the cell line characteristics and drug specific dose responses [25].…”

“…Cancer cell line-based models for these combination therapies are easy and inexpensive to perform using high-throughput drug screening protocols (HTS) to identify the most effective drug combination [25, 26]. HTS helps to explore the relation between the cell line characteristics and drug specific dose responses [25]. Chemogenomics is one such HTS based approach where large collection of anticancer chemical drugs are screened to identify biological targets.…”

Chemogenomic screening identifies the Hsp70 co-chaperone DNAJA1 as a hub for anticancer drug resistance

“…Thus, combination anticancer therapies have been used clinically for over 50 years to improve the responses achieved by monotherapies alone. Cancer cell line-based models for these combination therapies are easy and inexpensive to perform using high-throughput drug screening protocols (HTS) to identify the most effective drug combination 15,16 . HTS helps to explore the relationship between the cell line characteristics and drug specific dose responses 15 .…”

“…Cancer cell line-based models for these combination therapies are easy and inexpensive to perform using high-throughput drug screening protocols (HTS) to identify the most effective drug combination 15,16 . HTS helps to explore the relationship between the cell line characteristics and drug specific dose responses 15 . Chemogenomics is one such HTS-based approach where a large collection of anticancer chemical drugs are screened to identify biological targets.…”