Biology subjects

Johnson, G. N.

Publications and source records attributed to Johnson, G. N..

3 recordsLinked to original sources

bioRxiv2020

Cell-line-specific network models of ER+ breast cancer identify PI3Kα inhibitor sensitivity factors and drug combinations

Durable control of invasive solid tumors necessitates identifying therapeutic resistance mechanisms and effective drug combinations. A promising approach to tackle the cancer drug resistance problem is to build mechanistic mathematical models of the signaling network of cancer cells, and explicitly model the dynamics of information flow through this network under distinct genetic conditions and in response to perturbations. In this work, we used a network-based mathematical model to identify sensitivity factors and drug combinations for the PI3K inhibitor alpelisib, which was recently approved for ER+ PIK3CA mutant breast cancer. We experimentally validated the model-predicted efficacious combination of alpelisib and BH3 mimetics (e.g. MCL1 inhibitors) in ER+ breast cancer cell lines. We also experimentally validated the reduced sensitivity to alpelisib caused by FOXO3 knockdown, which is a novel potential resistance mechanism. Our experimental results showed cell line-specific sensitivity to the combination of alpelisib and BH3 mimetics, which was driven by the choice of BH3 mimetics. We find that cell lines were sensitive to the addition of either MCL1 inhibitor s63845 alone or in combination with BCL-XL/BCL-2 inhibitor navitoclax, and that the need for the combination of both BH3 mimetics was predicted by the expression of BCL-XL. Based on these results, we developed cell line-specific network models that are able to recapitulate the observed differential response to alpelisib and BH3 mimetics, and also incorporate the most recent knowledge on resistance and response to PI3K inhibitors. Overall, we present an approach for the development, experimental testing, and refining of mathematical models, which we apply to the context of PI3K inhibitor drug resistance in breast cancer. Our approach predicted and validated PI3K inhibitor sensitivity factors (FOXO3 knockdown) and drug combinations (BH3 mimetics), and illustrates that network-based mathematical models can contribute to overcoming the challenge of cancer drug resistance.

cancer biology↗

bioRxiv2020

A Failure Mode and Effect Analysis of plant metabolism reveals why cytosolic fumarase is required for temperature acclimation in Arabidopsis

Plants acclimate their photosynthetic capacity in response to changing environmental conditions. In Arabidopsis thaliana, photosynthetic acclimation to cold requires the accumulation of the organic acid fumarate, catalysed by a cytosolic fumarase FUM2, however the role of this is currently unclear. In this study, we use an integrated experimental and modelling approach to examine the role of FUM2 and fumarate across the physiological temperature range. Using physiological and biochemical analyses, we demonstrate that FUM2 is necessary for high as well as low temperature acclimation. To understand the role of FUM2 activity, we have adapted a reliability engineering technique, Failure Mode and Effect Analysis (FMEA), to formalize a rigorous approach for ranking metabolites according to the potential risk that they pose to the metabolic system. FMEA identifies fumarate as a low-risk metabolite. Its precursor, malate, is shown to be high-risk and liable to cause system instability. We conclude that the role of cytosolic fumarase, FUM2, is to provide a fail-safe, maintaining system stability under changing environmental conditions. We argue that FMEA is a technique which is not only useful in understanding plant metabolism, it can also be used to study reliability in other systems and aid the design of synthetic pathways.

plant biology↗

bioRxiv2019

The genomic landscape of intrinsic and acquired resistance to cyclin-dependent kinase 4/6 inhibitors in patients with hormone receptor positive metastatic breast cancer

Clinical resistance mechanisms to CDK4/6 inhibitors in HR+ breast cancer have not been clearly defined. Whole exome sequencing of 59 tumors with CDK4/6i exposure revealed multiple candidate resistance mechanisms including RB1 loss, activating alterations in AKT1, RAS, AURKA, CCNE2, ERBB2, and FGFR2, and loss of ER expression. In vitro experiments confirmed that these alterations conferred CDK4/6i resistance. Cancer cells cultured to resistance with CDK4/6i also acquired RB1, KRAS, AURKA, or CCNE2 alterations, which conferred sensitivity to AURKA, ERK, or CHEK1 inhibition. Besides inactivation of RB1, which accounts for [~]5% of resistance, seven of these mechanisms have not been previously identified as clinical mediators of resistance to CDK4/6 inhibitors in patients. Three of these--RAS activation, AKT activation, and AURKA activation--have not to our knowledge been previously demonstrated preclinically. Together, these eight mechanisms were present in 80% of resistant tumors profiled and may define therapeutic opportunities in patients. SignificanceWe identified eight distinct mechanisms of resistance to CDK4/6 inhibitors present in 80% of resistant tumors profiled. Most of these have a therapeutic strategy to overcome or prevent resistance in these tumors. Taken together, these findings have critical implications related to the potential utility of precision-based approaches to overcome resistance in many patients with HR+ MBC.

cancer biology↗