Biology subjects

Honeywell, M. E.

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

7 recordsLinked to original sources

bioRxiv2025

Genome-wide profiling identifies the genetic dependencies of cell death following EGFR inhibition

EGFR is a proto-oncogene that is mutationally activated in a variety of cancers. Small molecule inhibitors targeting EGFR can be effective in slowing the progression of disease, and in some settings these drugs even cause dramatic tumor regression. However, responses to EGFR inhibitors are rarely durable, and the mechanisms contributing to response variation remain unclear. In particular, several distinct mechanisms have been proposed for how EGFR inhibition activates cell death, and a consensus has yet to emerge. In this study, we use functional genomics with specialized analyses to infer how genetic perturbations effect the drug-induced death rate. Our data clarify that inhibition of PI3K signaling drives the lethality of EGFR inhibition. Inhibition of other pathways downstream of EGFR, including the RAS-MAPK pathway, promote growth suppression, but not the lethal effects of EGFR inhibitors. Taken together, our study reveals the first "reference map" for the genome-wide genetic dependencies of lethality for EGFR inhibitors.

cancer biology↗

bioRxiv2024

Pol II degradation activates cell death independently from the loss of transcription

Pol II-mediated transcription is essential for eukaryotic life. While loss of transcription is thought to be universally lethal, the associated mechanisms promoting cell death are not yet known. Here, we show that death following loss of Pol II is not caused by dysregulated gene expression. Instead, death occurs in response to the loss of Pol II protein itself, specifically loss of the enzymatic subunit, Rbp1. Loss of Pol II exclusively activates apoptosis, and expression of a transcriptionally inactive version of Rpb1 rescues cell viability. Using functional genomics, we identify a previously uncharacterized mechanism that regulates lethality following loss of Pol II, which we call the Pol II Degradation-dependent Apoptotic Response (PDAR). Using the genetic dependencies of PDAR, we identify clinically used drugs that owe their efficacy to a PDAR-dependent mechanism. Our findings unveil a novel apoptotic signaling response that contributes to the efficacy of a wide array of anti-cancer therapies.

cell biology↗

bioRxiv2023

Functional genomics reveals that a divergent genetic dependency signature is not essential to the synergism of molecular-targeted agent and chemotherapeutic combinations in gastric cancer cells

The rational combination of anticancer agents is critical to improving patient outcomes in cancer. Nonetheless, most combination regimens in the clinic result from empirical methodologies disregarding insight into the mechanism of action and missing the opportunity to improve therapy outcomes incrementally. Deciphering the genetic dependencies and vulnerabilities responsible for synergistic interactions is crucial for rationally developing effective anticancer drug combinations. Hence, we screened pairwise pharmacological interactions between molecular-targeted agents and conventional chemotherapeutics and examined the genome-scale genetic dependencies in gastric adenocarcinoma cell models. Since this type of cancer is mainly chemoresistant and incurable, clinical situations demand effective combination strategies. Our pairwise combination screen revealed SN38/erlotinib as the drug pair with the most robust synergism. Genome-wide CRISPR screening and a shRNA-based signature assay indicated that the genetic dependency/vulnerability signature of SN38/erlotinib is the same as SN38 alone. Additional investigation revealed that the enhanced cell death with improved death kinetics caused by the SN38/erlotinib combination is surprisingly due to erlotinibs off-target effect that inhibits ABCG2 but not its on-target effect on EGFR. Our results confirm that a genetic dependency signature different from the single-drug application may not be necessary for the synergistic interaction of molecular-targeted agents with conventional chemotherapeutics in gastric adenocarcinoma. The findings also demonstrated the efficacy of functional genomics approaches in unveiling biologically validated mechanisms of pharmacological interactions. SignificanceFunctional genomics approaches efficiently demonstrated an off-target dependency of the synergistic interaction of erlotinib with SN38 in gastric adenocarcinoma cell models.

cancer biology↗

bioRxiv2023

p53 controls choice between apoptotic and non-apoptotic death following DNA damage

DNA damage can activate apoptotic and non-apoptotic forms of cell death; however, it remains unclear what features dictate which type of cell death is activated. We report that p53 controls the choice between apoptotic and non-apoptotic death following exposure to DNA damage. In contrast to the conventional model, which suggests that p53-deficient cells should be resistant to DNA damage-induced cell death, we find that p53-deficient cells die at high rates following DNA damage, but exclusively using non-apoptotic mechanisms. Our experimental data and computational modeling reveal that non-apoptotic death in p53-deficient cells has not been observed due to use of assays that are either insensitive to cell death, or that specifically score apoptotic cells. Using functional genetic screening - with an analysis that enables computational inference of the drug-induced death rate - we find in p53-deficient cells that DNA damage activates a mitochondrial respiration-dependent form of cell death, called MPT-driven necrosis. Cells deficient for p53 have high basal respiration, which primes MPT-driven necrosis. Finally, using metabolite profiling, we identified mitochondrial activity-dependent metabolic vulnerabilities that can be targeted to potentiate the lethality of DNA damage specifically in p53-deficient cells. Our findings reveal how the dual functions of p53 in regulating mitochondrial activity and the DNA damage response combine to facilitate the choice between apoptotic and non-apoptotic death.

cell biology↗

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↗