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Heath, J. R.

Publications and source records attributed to Heath, J. R..

3 recordsLinked to original sources

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

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 BRAFV600E mutant patient-derived melanoma cancer cells take between drug-naive 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-naive 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-naive 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.

bioengineering

Kinetic Inference Resolves Epigenetic Mechanism of Drug Resistance in Melanoma

Drug-induced dedifferentiation towards a drug-tolerant persister state is a common mechanism cancer cells exploit to escape therapies, posing a significant obstacle to sustained therapeutic efficacy. The dynamic coordination of epigenomic and transcriptomic programs at the early-stage of drug exposure, which initiates and orchestrates these reversible dedifferentiation events, remains largely unexplored. Here we employ high-temporal-resolution multi-omics profiling, information-theoretic approaches, and dynamic system modeling to probe these processes in BRAF-mutant melanoma models and patient specimens. We uncover a hysteretic transition trajectory of melanoma cells in response to oncogene inhibition and subsequent release, driven by the sequential operation of two tightly coupled transcriptional waves, which orchestrate genome-scale chromatin state reconfiguration. Modeling of the transcriptional wave interactions predicts NF-{kappa}B/RelA-driven chromatin remodeling as the underlying mechanism of cell-state dedifferentiation, a finding we validate experimentally. Our results identify critical RelA-target genes that are epigenetically modulated to drive this process, establishing a quantitative epigenome gauge to measure cell-state plasticity in melanomas, which supports the potential use of drugs targeting epigenetic machineries to potentiate oncogene inhibition. Extending our investigation to other cancer models, we identify oxidative stress-mediated NF-{kappa}B/RelA activation as a common mechanism driving cellular transitions towards drug-tolerant persister states, revealing a novel and pivotal role for the NF-{kappa}B signaling axis in linking cellular oxidative stress to cancer progression.

cancer biology

MATE-Seq: Microfluidic Antigen-TCR Engagement Sequencing

Adaptive immunity is based on peptide antigen recognition. Our ability to harness the immune system for therapeutic gain relies on the discovery of the T cell receptor (TCR) genes that selectively target antigens from infections, mutated proteins, and foreign agents. Here we present a method that selectively labels peptide antigen-specific CD8+ T-cells in human blood using magnetic nanoparticles functionalized with peptide-MHC tetramers, isolates these specific cells within an integrated microfluidic device, and directly amplifies the TCR genes for sequencing. Critically, the identity of the peptide recognized by the TCR is preserved, providing the link between peptide and gene. The platform requires inputs on the order of just 100,000 CD8+ T cells, can be multiplexed for simultaneous analysis of multiple peptides, and performs sorting and isolation on chip. We demonstrate 1000-fold sensitivity enhancement of antigen-specific T-cell receptor detection and simultaneous capture of two virus antigen-specific T-cell receptors from samples of human blood.

immunology