Skip to main content
eScholarship
Open Access Publications from the University of California

DRUG-NEM: Optimizing drug combinations using single-cell perturbation response to account for intratumoral heterogeneity.

  • Author(s): Anchang, Benedict
  • Davis, Kara L
  • Fienberg, Harris G
  • Williamson, Brian D
  • Bendall, Sean C
  • Karacosta, Loukia G
  • Tibshirani, Robert
  • Nolan, Garry P
  • Plevritis, Sylvia K
  • et al.
Abstract

An individual malignant tumor is composed of a heterogeneous collection of single cells with distinct molecular and phenotypic features, a phenomenon termed intratumoral heterogeneity. Intratumoral heterogeneity poses challenges for cancer treatment, motivating the need for combination therapies. Single-cell technologies are now available to guide effective drug combinations by accounting for intratumoral heterogeneity through the analysis of the signaling perturbations of an individual tumor sample screened by a drug panel. In particular, Mass Cytometry Time-of-Flight (CyTOF) is a high-throughput single-cell technology that enables the simultaneous measurements of multiple ([Formula: see text]40) intracellular and surface markers at the level of single cells for hundreds of thousands of cells in a sample. We developed a computational framework, entitled Drug Nested Effects Models (DRUG-NEM), to analyze CyTOF single-drug perturbation data for the purpose of individualizing drug combinations. DRUG-NEM optimizes drug combinations by choosing the minimum number of drugs that produce the maximal desired intracellular effects based on nested effects modeling. We demonstrate the performance of DRUG-NEM using single-cell drug perturbation data from tumor cell lines and primary leukemia samples.

Main Content
Current View