Trajectories from Snapshots: Integrated proteomic and metabolic single-cell assays reveal multiple independent adaptive responses to drug tolerance in a BRAF-mutant melanoma cell line
Year: 2019
Type: preprint
Abstract: The determination of individual cell trajectories through a high-dimensional cell-state space is an outstanding challenge, with relevance towards understanding biological changes ranging from cellular differentiation to epigenetic (adaptive) responses of diseased cells to drugging. We report on a combined experimental and theoretic method for determining the trajectories that specific highly plastic BRAF V600E mutant patient-derived melanoma cancer cells take between drug-naïve and drug-tolerant states. Recent studies have implicated non-genetic, fast-acting resistance mechanisms are activated in these cells following BRAF inhibition. While single-cell highly multiplex omics tools can yield snapshots of the cell state space landscape sampled at any given time point, individual cell trajectories must be inferred from a kinetic series of snapshots, and that inference can be confounded by stochastic cell state switching. Using a microfludic-based single-cell integrated proteomic and metabolic assay, we assayed for a panel of signaling, phenotypic, and metabolic regulators at four time points during the first five days of drug treatment. Dimensional reduction of the resultant data set, coupled with information theoretic analysis, uncovered a complex cell state landscape and identified two distinct paths connecting drug-naïve and drug-tolerant states. Cells are shown to exclusively traverse one of the two pathways depending on the level of the lineage restricted transcription factor MITF in the drug-naïve cells. The two trajectories are associated with distinct signaling and metabolic susceptibilities, and are independently druggable. Our results update the paradigm of adaptive resistance development in an isogenic cell population and offer insight into the design of more effective combination therapies.
DOI: 10.1101/767988
Authors: Yapeng Su, Guideng Li, Melissa E. Ko, Hanjun Cheng, Ronghui Zhu, Min Xue, Jessica Wang, Jihoon W. Lee, Luke Frankiw, Alexander Xu, Stephanie Wong, Lidia Robert, Kaitlyn Takata, Sui Huang, Antoni Ribas, Raphael Levine, Garry P. Nolan, Wei Wei, Sylvia K. Plevritis, David Baltimore, James R. Heath
Institutions: California Institute of Technology, Institute for Systems Biology, Chinese Academy of Medical Sciences & Peking Union Medical College, Suzhou Institute of Systems Medicine, Institute of Basic Medical Sciences of the Chinese Academy of Medical Sciences, Stanford Medicine, Stanford University, University of California, Riverside, University of California, Los Angeles, UCLA Jonsson Comprehensive Cancer Center, Hebrew University of Jerusalem
Language: English
Topic: Melanoma and MAPK Pathways
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W2972340258