Biology subjects

Johnson, G. L.

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

14 recordsLinked to original sources

bioRxiv2026

Vulnerability of triple negative breast cancer to daraxonrasib pan-RAS(on) inhibition

Triple-Negative Breast Cancer (TNBC) is a clinical subtype where aberrant expression of receptor tyrosine kinases (RTKs) leads to the activation of the RAS-RAF-MEK-ERK pathway contributing to tumor progression. Therapies targeting components of the RAF-MEK-ERK pathway in TNBC have been disappointing due to rapid onset of adaptive reprogramming of the RTK landscape leading to pathway reactivation. To overcome the dynamic heterogeneity of RTK expression and their convergence in activating RAS, treatment with the pan-RAS(on) inhibitor daraxonrasib (RMC-6236), which inhibits RAS-GTP regulation of RAF kinases, inhibited proliferation independent of TNBC kinotype or oncogenic RAS mutation in three of four TNBC cell lines in vitro and two patient-derived TNBC xenografts in mice. Daraxonrasib in combination with the MEK inhibitor trametinib prevented reactivation of the RAF-MEK-ERK pathway observed with each inhibitor alone and further enhanced inhibition of tumor growth in TNBC cell lines and xenografts. Inhibiting pan-RAS(on) RAS-GTP, with daraxonrasib, alone or in combination with a MEK inhibitor, provides a new strategy for the treatment of TNBC that inhibits RTK activation of the RAS-RAF-MEK-ERK pathway and tumor proliferation.

cancer biology↗

bioRxiv2026

Transcriptomic profiling of mouse mammary tumors enables prognostic and predictive biomarker discovery for human breast cancers

The development and validation of prognostic and predictive biomarkers in breast cancer is limited by the availability of well-annotated datasets linking tumor molecular features to treatment response and survival outcomes. To address this need, we generated an extensive mouse models dataset comprised of 26 immunocompetent mammary tumor models spanning diverse genetic backgrounds, epithelial-mesenchymal states, the basal-luminal axis, and distinct immune microenvironments. For each model, we measured survival under no treatment, immune checkpoint inhibition (ICI), and carboplatin/paclitaxel chemotherapy. We performed RNA-seq on baseline tumors and on 7-day on-treatment samples for both regimens. Using baseline murine tumor gene expression features, we trained a machine learning Elastic Net model that predicted survival outcomes on multiple human breast cancer datasets with performance comparable to that of existing prognostic assays. We next trained models for ICI benefit, using either the untreated or 7-day ICI treated samples; both models predicted ICI benefit on human ICI treated datasets, with the 7-day treated tumor model showing better performance. We also developed a predictor of carboplatin/paclitaxel response that performed well in mice but did not generalize to human chemotherapy cohorts. Finally, we compared multiple computational approaches, including XGBoost, random forests, and support vector regression; all methods successfully predicted survival outcomes, with Elastic Net offering the best performance and interpretability. These results indicate conserved cancer biology between mouse and human tumors for prognosis and ICI response and establish this large preclinical dataset with linked phenotypic and genomic data, as a resource for benchmarking computational methods for survival prediction. SignificanceThe development of a genomically and phenotypically diverse murine tumor dataset with linked treatment outcomes establishes a robust translational resource to develop, test, and benchmark clinically relevant prognostic and therapeutic response biomarkers.

cancer biology↗

bioRxiv2025

The MEK inhibitor trametinib incurs mitochondrial injury and induces innate immune responses in the mouse heart

Trametinib (Trm) is a highly selective MEK inhibitor that potently and persistently abrogates ERK1/2 activation. Trm initially was used to treat BRAF V600E-mutated melanoma but its FDA-approved indications are expanding rapidly. Trm generally is well tolerated but it can cause dose-limiting cardiomyopathy and heart failure. Here we characterize a mouse model of Trm cardiotoxicity using complementary in vitro approaches to show that Trm induces mitochondrial dysfunction in cardiomyocytes and some cancer cell types. In vivo, Trm caused contractile dysfunction within 3 days and heart failure within 2 weeks. High resolution respirometry using isolated cardiac mitochondria revealed that Trm compromises oxidative metabolism, in part through blunted activity of Electron Transport System Complexes. Trm-mediated mitochondrial injury led to the release of mitochondrial Damage-Associated Molecular Patterns including mitochondrial DNA in both mice and humans, triggering activation of canonical innate immune pathways including cGAS-STING. In multiple rodent and human cardiomyocyte platforms, Trm diminished mitochondrial respiratory capacity at nanomolar concentrations but this lesion was reversed by expression of a phosphomimetic STAT3-S727 construct. We also found that Trm induced mitochondrial dysfunction in some but not all cancer cell lines, identifying a previously unrecognized effect that could contribute to Trms anti-cancer efficacy.

physiology↗

bioRxiv2024

Kinase Plasticity in Response to Vandetanib Enhances Sensitivity to Tamoxifen and Identifies Co-Treatment Strategies in Estrogen Receptor Positive Breast Cancer

Resistance to endocrine therapy (ET) is common in estrogen receptor-positive (ER+) breast cancer. Multiple studies have demonstrated that upregulation of MAPK signaling pathways contributes to ET resistance. Herein we show that vandetanib treatment suppresses MAPK signaling and enhances sensitivity to ET across ET-sensitive and ET-resistant ER+ cell lines and patient derived organoids. Vandetanib treatment reprograms transcription toward a less proliferative, more estrogen responsive, Luminal-A like state by enriching ER chromatin binding at canonical estrogen response elements. Multiplexed kinase inhibitor beads-mass spectrometry (MIB/MS) revealed kinase network reprogramming, including upregulation of PI3K and HER2 activity, as shared adaptive resistance mechanisms to vandetanib treatment. Co-treatment with the HER2 inhibitor lapatinib, further enhanced sensitivity to vandetanib. Using an operating room-to-laboratory short-term ex-vivo assay coupled to single-cell RNA sequencing, we demonstrate conserved gene expression changes in primary tumor cells, including increased HER2 activity signatures, following vandetanib treatment. Vandetanib sensitivity signatures were generated from cell line and primary human tumor cells which correlate with vandetanib sensitivity in ER+ patient-derived organoid and xenograft models. Future clinical trials of vandetanib in ER+ breast cancer should include rationally designed co-treatments based on adaptive resistance pathways, including HER2, and evaluate response signatures as biomarkers predicting patients most likely to benefit. SIGNIFICANCEVandetanib enhances sensitivity to tamoxifen in ER+ breast cancer by reprograming ER gene regulation and kinase signaling networks which define gene expression signatures associated with response and identify targetable adaptive resistance pathways.

cancer biology↗

bioRxiv2024

Quantitative proteomic mass spectrometry of protein kinases to determine dynamic heterogeneity of the human kinome

The kinome is a dynamic system of kinases regulating signaling networks in cells and dysfunction of protein kinases contributes to many diseases. Regulation of the protein expression of kinases alters cellular responses to environmental changes and perturbations. We configured a library of 672 proteotypic peptides to quantify >300 kinases in a single LC-MS experiment using ten micrograms protein from human tissues including biopsies. This enables absolute quantitation of kinase protein abundance at attomole-femtomole expression levels, requiring no kinase enrichment and less than ten micrograms of starting protein from flash-frozen and formalin fixed paraffin embedded tissues. Breast cancer biopsies, organoids, and cell lines were analyzed using the SureQuant method, demonstrating the heterogeneity of kinase protein expression across and within breast cancer clinical subtypes. Kinome quantitation was coupled with nanoscale phosphoproteomics, providing a feasible method for novel clinical diagnosis and understanding of patient kinome responses to treatment.

biochemistry↗

bioRxiv2023

Discovery and Optimization of Narrow Spectrum Inhibitors of Tousled Like Kinase 2 (TLK2) Using Quantitative Structure Activity Relationships

The oxindole scaffold has been the center of several kinase drug discovery programs, some of which have led to approved medicines. A series of two oxindole matched pairs from the literature were identified where TLK2 was a potent off-target kinase. The oxindole as long been considered a promiscuous inhibitor template, but across these 4 specific literature oxindoles TLK2 activity was consistent, while the kinome profile was radically different from narrow to broad spectrum coverage. We synthesized a large series of analogues and through quantitative structure-activity relationship (QSAR) analysis, water mapping of the kinase ATP binding sites, small-molecule x-ray structural analysis and kinome profiling, narrow spectrum, sub-family selective, chemical tool compounds were identified to enable elucidation of TLK2 biology.

pharmacology and toxicology↗

bioRxiv2023

Combined kinome inhibition states are predictive of cancer cell line sensitivity to kinase inhibitor combination therapies

Protein kinases are a primary focus in targeted therapy development for cancer, owing to their role as regulators in nearly all areas of cell life. Kinase inhibitors are one of the fastest growing drug classes in oncology, but resistance acquisition to kinase-targeting monotherapies is inevitable due to the dynamic and interconnected nature of the kinome in response to perturbation. Recent strategies targeting the kinome with combination therapies have shown promise, such as the approval of Trametinib and Dabrafenib in advanced melanoma, but similar empirical combination design for less characterized pathways remains a challenge. Computational combination screening is an attractive alternative, allowing in-silico screening prior to in-vitro or in-vivo testing of drastically fewer leads, increasing efficiency and effectiveness of drug development pipelines. In this work, we generate combined kinome inhibition states of 40,000 kinase inhibitor combinations from kinobeads-based kinome profiling across 64 doses. We then integrated these with baseline transcriptomics from CCLE to build robust machine learning models to predict cell line sensitivity from NCI-ALMANAC across nine cancer types, with model accuracy R2 [~] 0.75-0.9 after feature selection using elastic-net regression. We further validated the models ability to extend to real-world examples by using the best-performing breast cancer model to generate predictions for kinase inhibitor combination sensitivity and synergy in a PDX-derived TNBC cell line and saw reasonable global accuracy in our experimental validation (R2 [~] 0.7) as well as high accuracy in predicting synergy using four popular metrics (R2 [~] 0.9). Additionally, the model was able to predict a highly synergistic combination of Trametinib (MEK inhibitor) and Omipalisib (PI3K inhibitor) for TNBC treatment, which incidentally was recently in phase I clinical trials for TNBC. Our choice of tree-based models over networks for greater interpretability also allowed us to further interrogate which specific kinases were highly predictive of cell sensitivity in each cancer type, and we saw confirmatory strong predictive power in the inhibition of MAPK, CDK, and STK kinases. Overall, these results suggest that kinome inhibition states of kinase inhibitor combinations are strongly predictive of cell line responses and have great potential for integration into computational drug screening pipelines. This approach may facilitate the identification of effective kinase inhibitor combinations and accelerate the development of novel cancer therapies, ultimately improving patient outcomes.

systems biology↗

bioRxiv2022

En1 and Lmx1b do not recapitulate embryonic dorsal-ventral limb patterning functions during mouse digit tip regeneration

The mouse digit tip is a complex tissue that is capable of regeneration after amputation. How the regenerated digit tip is patterned is unknown, but a long-standing hypothesis in the field of regeneration proposes that developmental patterning mechanisms are re-used during regeneration. The digit tip bone exhibits strong dorsal-ventral (DV) polarity, so we focus on Engrailed 1 (En1) and LIM homeobox transcription factor 1B (Lmx1b), two well-studied transcription factors necessary for DV patterning during limb development. We investigate if En1 and Lmx1b are re-expressed during regeneration in a developmental-like spatially restricted pattern, and if they direct DV morphology of the regenerated digit tip. We find that both En1 and Lmx1b are expressed in the regenerating mouse digit tip epithelium and mesenchyme, respectively, but without DV polarity. We use conditional genetics and quantitative analysis of digit tip bone morphology to determine that genetic deletion of En1 or Lmx1b in adult digit tip regeneration modestly reduces bone regeneration but does not affect DV patterning of the regenerate. Collectively, our data suggest that while En1 and Lmx1b are re-expressed during mouse digit tip regeneration, they do not define the DV axis during regeneration.

developmental biology↗

bioRxiv2021

Kinome state is predictive of cell viability in pancreatic cancer tumor and stroma cell lines

Numerous aspects of cellular signaling are regulated by the kinome - the network of over 500 protein kinases that guides and modulates information transfer throughout the cell. The key role played by both individual kinases and assemblies of kinases organized into functional subnetworks leads to kinome dysregulation being a key driver of many diseases, particularly cancer. In the case of pancreatic ductal adenocarcinoma (PDAC), a variety of kinases and associated signaling pathways have been identified for their key role in the establishment of disease as well as its progression. However, the identification of additional relevant therapeutic targets has been slow and is further confounded by interactions between the tumor and the surrounding tumor microenvironment. Fundamentally, it is an open question as to the degree to which knowledge of the state of the kinome at the protein level is able to provide insight into the downstream phenotype of the cell. In this work, we attempt to link the state of the kinome, or kinotype, with cell viability in representative PDAC tumor and stroma cell lines. Through the application of both regression and classification models to independent kinome perturbation and kinase inhibitor cell screen data, we find that the inferred kinotype of a cell has a significant and predictive relationship with cell viability. While regression models perform poorly, we find that classification approaches are able to predict drug viability effects. We further find that models are able to identify a set of kinases whose behavior in response to perturbation drive the majority of viability responses in these cell lines. Using the models to predict new compounds with cell viability effects and not in the initial data set, we conducted a validation screen that confirmed the accuracy of the models. These results suggest that characterizing the state of the protein kinome provides significant opportunity for better understanding signaling behavior and downstream cell phenotypes, as well as providing insight into the broader design of potential therapy design for PDAC.

bioinformatics↗

bioRxiv2020

Limited inhibition of multiple nodes in a driver network blocks metastasis

Metastasis suppression by high-dose, multi-drug targeting is largely unsuccessful due to network heterogeneity and compensatory network activation. Here we show that targeting driver network signaling capacity by limited inhibition of its core pathways is a more effective anti-metastatic strategy. This principle underlies the action of a physiological metastasis suppressor, Raf Kinase Inhibitory Protein, which moderately decreases stress-regulated MAP kinase network activity, reducing the output to metastatic transcription factor BACH1 and motility-related target genes. We developed a low-dose four-drug mimic that blocks metastatic colonization in mouse breast cancer models and increases survival. Experiments and network flow modeling show: 1) limited inhibition of multiple pathways is required to overcome variation in MAPK network topology and suppress signaling output across heterogeneous tumor cells, and 2) restricting inhibition of individual kinases dissipates surplus signal, preventing threshold activation of compensatory kinase networks. This low-dose multi-drug approach to decrease signaling capacity of driver networks represents a transformative, clinically-relevant strategy for anti-metastatic treatment.

cancer biology↗

bioRxiv2020

Miniaturized head-mounted device for whole cortex mesoscale imaging in freely behaving mice

The advent of genetically encoded calcium indicators, along with surgical preparations such as thinned skulls or refractive index matched skulls, have enabled mesoscale cortical activity imaging in head-fixed mice. Such imaging studies have revealed complex patterns of coordinated activity across the cortex during spontaneous behaviors, goal-directed behavior, locomotion, motor learning, and perceptual decision making. However, neural activity during unrestrained behavior significantly differs from neural activity in head-fixed animals. Whole-cortex imaging in freely behaving mice will enable the study of neural activity in a larger, more complex repertoire of behaviors not possible in head-fixed animals. Here we present the "Mesoscope," a wide-field miniaturized, head-mounted fluorescence microscope compatible with transparent polymer skulls recently developed by our group. With a field of view of 8 mm x 10 mm and weighing less than 4 g, the Mesoscope can image most of the mouse dorsal cortex with resolution ranging from 39 to 56 {micro}m. Stroboscopic illumination with blue and green LEDs allows for the measurement of both fluorescence changes due to calcium activity and reflectance signals to capture hemodynamic changes. We have used the Mesoscope to successfully record mesoscale calcium activity across the dorsal cortex during sensory-evoked stimuli, open field behaviors, and social interactions. Finally, combining the mesoscale imaging with electrophysiology enabled us to measure dynamics in extracellular glutamate release in the cortex during the transition from wakefulness to natural sleep.

neuroscience↗

bioRxiv2019

Cellular heterogeneity and lineage restriction during mouse digit tip regeneration at single cell resolution

Innate regeneration following digit tip amputation is one of the few examples of epimorphic regeneration in mammals. Digit tip regeneration is mediated by the blastema, the same structure invoked during limb regeneration in some lower vertebrates. By genetic lineage analyses in mice, the digit tip blastema has been defined as a population of heterogeneous, lineage restricted progenitor cells. These previous studies, however, do not comprehensively evaluate blastema heterogeneity or address lineage restriction of closely related cell types. In this report we present single cell RNA sequencing of over 38,000 cells from mouse digit tip blastemas and unamputated control digit tips and generate an atlas of the cell types participating in digit tip regeneration. We define the differentiation trajectories of vascular, monocytic, and fibroblastic lineages over regeneration, and while our data confirm broad lineage restriction of progenitors, our analysis reveals an early blastema fibroblast population expressing a novel regeneration-specific gene, Mest.

molecular biology↗

bioRxiv2018

Design of a GAK/EGFR inhibitor set to interrogate the relationship of EGFR and GAK in chordoma

We describe the design of a set of inhibitors to investigate the relationship between cyclin G associated kinase (GAK) and epidermal growth factor receptor (EGFR) in chordoma bone cancers. These compounds were characterized both in vitro and using in cell target engagement assays. The most potent chordoma inhibitors were further characterized in a kinome-wide screen demonstrating narrow spectrum profiles.

pharmacology and toxicology↗

bioRxiv2017

Proteomic Analysis Defines Kinase Taxonomies Specific For Subtypes Of Breast Cancer

Multiplexed small molecule inhibitors covalently bound to Sepharose beads (MIBs) were used to capture functional kinases in luminal, HER2-enriched and triple negative, basal-like and claudin-low breast cancer cell lines and tumors. Kinase MIB-binding profiles at baseline without perturbation proteomically distinguished the four breast cancer subtypes. Kinases lacking defined functions in breast cancer were highly represented in the MIB-binding taxonomies. We show that these understudied kinases, whose disease associations and pharmacology are generally unexplored, are integrated in kinase signaling subnetworks with kinases that have been previously well characterized in breast cancer. Computationally it was possible to define subtypes using profiles of less than 50 of the more than 300 kinases bound to MIBs that included understudied as well as metabolic and lipid kinases. Furthermore, analysis of MIB-binding profiles established potential functional annotations for these understudied kinases. Thus, comprehensive MIBs-based capture of kinases provides a unique proteomics-based method for integration of poorly characterized kinases of the understudied kinome into functional subnetworks in breast cancer cells and tumors that is not possible using genomic strategies. The MIB-binding profiles readily defined subtype-selective differential adaptive kinome reprogramming in response to targeted kinase inhibition, demonstrating how MIB profiles can be used in determining dynamic kinome changes that result in subtype selective phenotypic state changes.

cancer biology↗