Biology subjects

East, M. P.

Publications and source records attributed to East, M. P..

10 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↗

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↗

bioRxiv2022

SMALL MOLECULE CLPP AGONISTS INDUCE SENESCENCE AND ALTER TRAIL-MEDIATED APOPTOTIC RESPONSE OF TRIPLE-NEGATIVE BREAST CANCER CELLS

Imipridones are a novel class of anticancer drugs with promising antiproliferative effects in several cancer cell types, including breast cancer. Recent studies identified the mitochondrial ATP-dependent caseinolytic peptidase P (ClpP) as the target for imipridones and related analogs. Despite these findings, the specific processes by which ClpP activators inhibit cancer cell growth remain poorly understood. Here we report that two structurally distinct ClpP activators, ONC201 and TR-57, promote senescence in SUM159 and MDA-MB-231 triple-negative breast cancer (TNBC) cell lines. Induction of senescence was measured through {beta}-galactosidase assays and confirmed by the increase of H2A.X phosphorylation, hypophosphorylation of retinoblastoma protein (Rb), upregulation of multiple interleukin mRNAs and other markers. The level of senescence induced by these compounds was equivalent to that observed with the CDK4/6 inhibitor and positive control abemaciclib. To confirm the crucial role of ClpP activation in senescence induction, we generated ClpP null TNBC cell lines using CRISPR interference (CRISPRi). Neither ONC201 nor TR-57 induced senescence in the ClpP null models. Incubation of WT cells with ClpP activators led to a reduction in the levels of apoptosis-related proteins like XIAP, SMAC/DIABLO, Survivin, DR4 and DR5, which correlated with the lack of apoptosis observed in these cells. Interestingly, treatment with TR-57 strongly reduced apoptosis induced by staurosporine but increased sensitivity to tumor necrosis factor-related apoptosis-inducing ligand (TRAIL). To investigate the enhanced effects of TRAIL, we examined the expression of Wee1 in senescent cells and found that both TR-57 and abemaciclib down-regulated Wee1. Addition of a Wee1 inhibitor partially sensitized cells to TRAIL suggesting the importance of Wee1 in this process. In summary, we show that ClpP activators induce senescence in a ClpP-dependent manner and that combined treatment of ClpP activators with TRAIL provides an effective approach to eliminate malignant senescent cells in vitro. HIGHLIGHTSO_LITreatment of TNBC cells with ClpP activators induces senescence in vitro C_LIO_LIInduction of senescence is ClpP dependent C_LIO_LIActivation of ClpP leads to changes in mRNA levels of senescence associated cytokines C_LIO_LISenescent TNBC cells are sensitized to TRAIL mediated apoptosis C_LI

cancer biology↗

bioRxiv2021

The ARF GAPs ELMOD1 and ELMOD3 act at the Golgi and Cilia to Regulate Ciliogenesis and Ciliary Protein Traffic

ELMODs are a family of three mammalian paralogs that display GTPase activating protein (GAP) activity towards a uniquely broad array of ADP-ribosylation factor (ARF) family GTPases that includes ARF-like (ARL) proteins. ELMODs are ubiquitously expressed in mammalian tissues, highly conserved across eukaryotes, and ancient in origin, being present in the last eukaryotic common ancestor. We described functions of ELMOD2 in immortalized mouse embryonic fibroblasts (MEFs) in the regulation of cell division, microtubules, ciliogenesis, and mitochondrial fusion. Here, using similar strategies with the paralogs ELMOD1 and ELMOD3, we identify novel functions and locations of these cell regulators and compare them to those of ELMOD2, allowing determination of functional redundancy among the family members. We found strong similarities in phenotypes resulting from deletion of either Elmod1 or Elmod3 and marked differences from those arising in Elmod2 deletion lines. Deletion of either Elmod1 or Elmod3 results in the decreased ability of cells to form primary cilia, loss of a subset of proteins from cilia, and accumulation of some ciliary proteins at the Golgi, predicted to result from compromised traffic from the Golgi to cilia. These phenotypes are reversed upon expression of activating mutants of either ARL3 or ARL16, linking their roles to ELMOD1/3 actions. Thus, we believe that ELMOD1 and ELMOD3 perform multiple functions in cells, most prominently linked to ciliary biology and Golgi-ciliary traffic, and likely acting from more than one cellular location.

cell 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↗

bioRxiv2018

SGC-GAK-1: a chemical probe for cyclin G associated kinase (GAK)

We describe SGC-GAK-1 (11), a potent, selective, and cell-active inhibitor of cyclin G associated kinase (GAK), together with a structurally-related negative control SGC-GAK-1N (14). SGC-GAK-1 is highly selective in a kinome-wide screen, but cellular engagement assays defined RIPK2 as a collateral target. We identified 18 as a potent inhibitor of RIPK2 lacking GAK activity. Together, the chemical probe set of 11, 14, and 18 can be used to interrogate the cellular biology of GAK inhibition.

cell biology↗

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↗