Biology subjects

Honeywell, M. E.

Publications and source records attributed to Honeywell, M. E..

3 recordsLinked to original sources

bioRxiv2020

ELP-dependent expression of MCL1 promotes resistance to EGFR inhibition in triple-negative breast cancer cells

Targeted therapies for the treatment of cancer are generally thought to exploit oncogene addiction, a phenomenon in which a single oncogene controls both the growth and survival of the tumor cell. Many well-validated examples of oncogene addiction exist; however, the utility of oncogene targeted therapies varies substantially by cancer context, even among cancers in which the targeted oncogene is similarly dysregulated. For instance, epidermal growth factor receptor (EGFR) signaling can be effectively targeted in EGFR-mutant non-small cell lung cancer (NSCLC), but not in triple-negative breast cancer (TNBC), where EGFR is activated to a similar degree. We find that EGFR controls a similar signaling/transcriptional network in TNBC and EGFR-mutant NSCLC cells, but only NSCLC cells respond to EGFR inhibition by activating cell death. To address this paradox and identify mechanisms that contribute to insensitivity to EGFR inhibition in TNBC, we performed a genome-wide CRISPR-Cas9 genetic knockout screen. Our screen identifies the Elongator (ELP) complex as a mediator of insensitivity to EGFR inhibition in TNBC. Depleting ELP proteins caused high levels of apoptotic cell death, in an EGFR inhibition-dependent manner. We find that the tRNA-modifying function of the ELP complex promotes drug insensitivity, by facilitating expression of the anti-apoptotic protein MCL1. Furthermore, pharmacological inhibition of MCL1 synergizes with EGFR inhibition across a panel of genetically diverse TNBC cells. Taken together, we find that TNBC "addiction" to EGFR signaling is masked by the ELP complex, and our study provides an actionable therapeutic strategy to overcome this resistance mechanism by co-targeting EGFR and MCL1. One sentence summaryThe Elongator Protein (ELP) Complex masks TNBC oncogene "addiction" to EGFR signaling, by promoting expression of the anti-apoptotic protein MCL1.

cancer biology↗

bioRxiv2020

Drug GRADE: an integrated analysis of population growth and cell death reveals drug- specific and cancer subtype-specific response profiles

In the pre-clinical evaluation of anti-cancer drugs, two different measurement approaches are used: relative viability, which scores an amalgam of growth arrest and cell death, and fractional viability, which more specifically scores the degree of cell killing. In this study, we directly quantify relationships between drug-induced growth inhibition and drug-induced cell death by counting live and dead cells over time using quantitative microscopy. We find that most drugs affect both growth and death, but with different proportions and with different relative timing. These features lead to a non-uniform and unpredictable relationship between the canonical relative and fractional drug response measurements. To unify these disparate measurements, we create a new data visualization and data analysis platform, called drug GRADE, which characterizes the degree to which cell death contributes to an observed reduction in population size for any given drug. Our new method reveals both drug- and genotype-specific drug responses, which are not captured using traditional pharmaco-metrics. Taken together, this study highlights the extremely idiosyncratic nature of drug-induced growth and cell death and provides a new analysis tool for quantitatively evaluating these behaviors.

systems biology↗

bioRxiv2019

Drug Combination Antagonism and Single Agent Dominance Result from Differences in Death Activation Kinetics

Therapeutic regimens for cancer generally involve drugs used in combinations. Most prior work has focused on identifying and understanding synergistic drug-drug interactions; however, understanding sources of antagonistic interactions remains an important and understudied issue. To enrich for antagonistic interactions and reveal common features of these drug combinations, we screened all pairwise combinations of drugs characterized as canonical activators of different forms of regulated cell death. We find that this network is strongly enriched for antagonistic interactions, and in particular, enriched for an extreme form of antagonism, which we call \"single agent dominance\". Single agent dominance refers to antagonisms in which a two drug combination phenocopies one of the two agents. We find that dominance results from differences in the cell death onset time, with dominant drugs inducing death earlier and at faster rates than their suppressed counterparts. Finally, we explored the mechanisms by which parthanatotic agents dominate apoptotic agents, finding that dominance in this scenario is caused by mutually exclusive and conflicting use of PARP1. Taken together, our study reveals death activation kinetics as a predictive feature of antagonism, due to inhibitory crosstalk between cell death pathways.

systems biology↗