Short-term cellular memory tunes the signaling responses of the chemokine receptor CXCR4

BTK inhibitors resistance in B cell malignancies: Mechanisms and potential therapeutic strategies

Bruton tyrosine kinase inhibitors (BTKi) have shown prominent clinical efficacy in patients with B cell malignancies, such as chronic lymphocytic leukemia, mantle cell lymphoma, diffuse large B cell lymphoma, and Waldenström's macroglobulinemia. Nevertheless, numerous factors contribute to BTKi resistance, encompassing genetic mutations, chromosomal aberrations, dysregulation of protein expression, tumor microenvironment, and metabolic reprogramming. Accordingly, potential therapeutic strategies have been explored to surmount BTKi resistance, including noncovalent BTKi, BTK proteolysis-targeting chimeras, and combination therapies. Herein, we summarize the mechanisms responsible for BTKi resistance as well as the current preclinical and clinical strategies to address BTKi resistance in B cell malignancies treatment.

Inhibiting CXCR4 reduces immunosuppressive effects of myeloid cells in breast cancer immunotherapy

Patients with triple negative breast cancer (TNBC) show only modest response rates to immune checkpoint inhibitor immunotherapy, motivating ongoing efforts to identify approaches to boost efficacy. Using an immunocompetent mouse model of TNBC, we investigated combination therapy with an anti-PD-1 immunotherapy antibody plus balixafortide, a cyclic peptide inhibitor of CXCR4. Cell-based assays demonstrated that balixafortide functions as an inverse agonist, establishing a mode of action distinct from most compounds targeting CXCR4. Combination anti-PD-1 plus balixafortide significantly reduced growth of orthotopic tumors and extended overall survival relative to single agent therapy or vehicle. Adding balixafortide to anti-PD-1 increased numbers of tertiary lymphoid structures, a marker of local tumor immune responses associated with favorable response to immunotherapy in TNBC. Single cell RNA sequencing revealed that combination anti-PD-1 plus balixafortide reduced T cell exhaustion and increased markers of effector T cell activity. Combination therapy also reduced signatures of immunosuppressive myeloid derived suppressor cells (MDSCs) in tumors. MDSCs isolated from mice treated with anti-PD-1 plus balixafortide showed reduced inhibition of T cell proliferation following ex vivo stimulation. These studies demonstrate that combining inhibition of CXCR4 with anti-PD-1 to enhances responses to checkpoint inhibitor immunotherapy in TNBC, supporting future clinical trials.

Inference of weak-form partial differential equations describing migration and proliferation mechanisms in wound healing experiments on cancer cells

Targeting signaling pathways that drive cancer cell migration or proliferation is a common therapeutic approach. A popular experimental technique, the scratch assay, measures the migration and proliferation-driven cell closure of a defect in a confluent cell monolayer. These assays do not measure dynamic effects. To improve analysis of scratch assays, we combine high-throughput scratch assays, video microscopy, and system identification to infer partial differential equation (PDE) models of cell migration and proliferation. We capture the evolution of cell density fields over time using live cell microscopy and automated image processing. We employ weak form-based system identification techniques for cell density dynamics modeled with first-order kinetics of advection-diffusion-reaction systems. We present a comparison of our methods to results obtained using traditional inference approaches on previously analyzed 1-dimensional scratch assay data. We demonstrate the application of this pipeline on high throughput 2-dimensional scratch assays and find that low levels of trametinib inhibit wound closure primarily by decreasing random cell migration by approximately 20%. Our integrated experimental and computational pipeline can be adapted for quantitatively inferring the effect of biological perturbations on cell migration and proliferation in various cell lines.

Characterizing heterogeneous single-cell dose responses computationally and experimentally using threshold inhibition surfaces and dose-titration assays

Single cancer cells within a tumor exhibit variable levels of resistance to drugs, ultimately leading to treatment failures. While tumor heterogeneity is recognized as a major obstacle to cancer therapy, standard dose-response measurements for the potency of targeted kinase inhibitors aggregate populations of cells, obscuring intercellular variations in responses. In this work, we develop an analytical and experimental framework to quantify and model dose responses of individual cancer cells to drugs. We first explore the connection between population and single-cell dose responses using a computational model, revealing that multiple heterogeneous populations can yield nearly identical population dose responses. We demonstrate that a single-cell analysis method, which we term a threshold inhibition surface, can differentiate among these populations. To demonstrate the applicability of this method, we develop a dose-titration assay to measure dose responses in single cells. We apply this assay to breast cancer cells responding to phosphatidylinositol-3-kinase inhibition (PI3Ki), using clinically relevant PI3Kis on breast cancer cell lines expressing fluorescent biosensors for kinase activity. We demonstrate that MCF-7 breast cancer cells exhibit heterogeneous dose responses with some cells requiring over ten-fold higher concentrations than the population average to achieve inhibition. Our work reimagines dose-response relationships for cancer drugs in an emerging paradigm of single-cell tumor heterogeneity.

Optimal phenotypic adaptation in fluctuating environments

Phenotypic adaptation is a universal feature of biological systems navigating highly variable environments. Recent empirical data support the role of memory-driven decision making in cellular systems navigating uncertain future nutrient landscapes, wherein a distinct growth phenotype emerges in fluctuating conditions. We develop a simple stochastic mathematical model to describe memory-driven cellular adaptation required for systems to optimally navigate such uncertainty. In this framework, adaptive populations traverse dynamic environments by inferring future variation from a memory of prior states, and memory capacity imposes a fundamental trade-off between the speed and accuracy of adaptation to new fluctuating environments. Our results suggest that the observed growth reductions that occur in fluctuating environments are a direct consequence of optimal decision making and result from bet hedging and occasional phenotypic-environmental mismatch. We anticipate that this modeling framework will be useful for studying the role of memory in phenotypic adaptation, including in the design of temporally varying therapies against adaptive systems.

Oscillatory ERK Signaling and Morphology Determine Heterogeneity of Breast Cancer Cell Chemotaxis via MEK-ERK and p38-MAPK Signaling Pathways

Chemotaxis, regulated by oscillatory signals, drives critical processes in cancer metastasis. Crucial chemoattractant molecules in breast cancer, CXCL12 and EGF, drive the activation of ERK and Akt. Regulated by feedback and crosstalk mechanisms, oscillatory signals in ERK and Akt control resultant changes in cell morphology and chemotaxis. While commonly studied at the population scale, metastasis arises from small numbers of cells that successfully disseminate, underscoring the need to analyze processes that cancer cells use to connect oscillatory signaling to chemotaxis at single-cell resolution. Furthermore, little is known about how to successfully target fast-migrating cells to block metastasis. We investigated to what extent oscillatory networks in single cells associate with heterogeneous chemotactic responses and how targeted inhibitors block signaling processes in chemotaxis. We integrated live, single-cell imaging with time-dependent data processing to discover oscillatory signal processes defining heterogeneous chemotactic responses. We identified that short ERK and Akt waves, regulated by MEK-ERK and p38-MAPK signaling pathways, determine the heterogeneous random migration of cancer cells. By comparison, long ERK waves and the morphological changes regulated by MEK-ERK signaling, determine heterogeneous directed motion. This study indicates that treatments against chemotaxis in consider must interrupt oscillatory signaling.

Computational modeling implicates protein scaffolding in p38 regulation of Akt

Cells process environmental cues by activating intracellular signaling pathways with numerous interconnections and opportunities for cross-regulation. We employed a systems biology approach to investigate intersections of kinase p38, a context-dependent tumor suppressor or promoter, with Akt and ERK, two kinases known to promote cell survival, proliferation, and drug resistance in cancer. Using live, single cell microscopy, multiplexed fluorescent reporters of p38, Akt, and ERK activities, and a custom automated image-processing pipeline, we detected marked heterogeneity of signaling outputs in breast cancer cells stimulated with chemokine CXCL12 or epidermal growth factor (EGF). Basal activity of p38 correlated inversely with amplitude of Akt and ERK activation in response to either ligand. Remarkably, small molecule inhibitors of p38 immediately decreased basal activities of Akt and ERK but increased the proportion of cells with high amplitude ligand-induced activation of Akt signaling. To identify mechanisms underlying cross-talk of p38 with Akt signaling, we developed a computational model incorporating subcellular compartmentalization of signaling molecules by scaffold proteins. Dynamics of this model revealed that subcellular scaffolding of Akt accounted for observed regulation by p38. The model also predicted that differences in the amount of scaffold protein in a subcellular compartment captured the observed single cell heterogeneity in signaling. Finally, our model predicted that reduction in kinase signaling can be accomplished by both scaffolding and direct kinase inhibition. However, scaffolding inhibition can potentiate future kinase activity by redistribution of pathway components, potentially amplifying oncogenic signaling. These studies reveal how computational modeling can decipher mechanisms of cross-talk between the p38 and Akt signaling pathways and point to scaffold proteins as central regulators of signaling dynamics and amplitude.

Emergence of synchronized multicellular mechanosensing from spatiotemporal integration of heterogeneous single-cell information transfer

Multicellular synchronization is a ubiquitous phenomenon in living systems. However, how noisy and heterogeneous behaviors of individual cells are integrated across a population toward multicellular synchronization is unclear. Here, we study the process of multicellular calcium synchronization of the endothelial cell monolayer in response to mechanical stimuli. We applied information theory to quantify the asymmetric information transfer between pairs of cells and defined quantitative measures to how single cells receive or transmit information within a multicellular network. Our analysis revealed that multicellular synchronization was established by gradual enhancement of information spread from the single cell to the multicellular scale. Synchronization was associated with heterogeneity in the cells' communication properties, reinforcement of the cells' state, and information flow. Altogether, we suggest a phenomenological model where cells gradually learn their local environment, adjust, and reinforce their internal state to stabilize the multicellular network architecture to support information flow from local to global scales toward multicellular synchronization.

MIF/CXCR4 signaling axis contributes to survival, invasion, and drug resistance of metastatic neuroblastoma cells in the bone marrow microenvironment

BACKGROUND

The bone marrow (BM) is the most common site of dissemination in patients with aggressive, metastatic neuroblastoma (NB). However, the molecular mechanisms underlying the aggressive behavior of NB cells in the BM niche are still greatly unknown. In the present study, we explored biological mechanisms that play a critical role in NB cell survival and progression in the BM and investigated potential therapeutic targets.

METHODS

Patient-derived bone marrow (BM) primary cultures were generated using fresh BM aspirates obtained from NB patients. NB cell lines were cultured in the presence of BM conditioned media containing cell-secreted factors, and under low oxygen levels (1% O₂) to mimic specific features of the BM microenvironment of high-risk NB patients. The BM niche was explored using cytokine profiling assays, cell migration-invasion and viability assays, flow cytometry and analysis of RNA-sequencing data. Selective pharmacological inhibition of factors identified as potential mediators of NB progression within the BM niche was performed in vitro and in vivo.

RESULTS

We identified macrophage migration inhibitory factor (MIF) as a key inflammatory cytokine involved in BM infiltration. Cytokine profiling and RNA-sequencing data analysis revealed NB cells as the main source of MIF in the BM, suggesting a potential role of MIF in tumor invasion. Exposure of NB cells to BM-conditions increased NB cell-surface expression of the MIF receptor CXCR4, which was associated with increased cell viability, enhanced migration-invasion, and activation of PI3K/AKT and MAPK/ERK signaling pathways. Moreover, subcutaneous co-injection of NB and BM cells enhanced tumor engraftment in mice. MIF inhibition with 4-IPP impaired in vitro NB aggressiveness, and improved drug response while delayed NB growth, improving survival of the NB xenograft model.

CONCLUSIONS

Our findings suggest that BM infiltration by NB cells may be mediated, in part, by MIF-CXCR4 signaling. We demonstrate the antitumor efficacy of MIF targeting in vitro and in vivo that could represent a novel therapeutic target for patients with disseminated high-risk NB.

Ultrasound-Induced Mechanical Compaction in Acoustically Responsive Scaffolds Promotes Spatiotemporally Modulated Signaling in Triple Negative Breast Cancer

Cancer cells continually sense and respond to mechanical cues from the extracellular matrix (ECM). Interaction with the ECM can alter intracellular signaling cascades, leading to changes in processes that promote cancer cell growth, migration, and survival. The present study used a recently developed composite hydrogel composed of a fibrin matrix and phase-shift emulsion, termed an acoustically responsive scaffold (ARS), to investigate effects of local mechanical properties on breast cancer cell signaling. Treatment of ARSs with focused ultrasound drives acoustic droplet vaporization (ADV) in a spatiotemporally controlled manner, inducing local compaction and stiffening of the fibrin matrix adjacent to the matrix-bubble interface. Combining ARSs and live single cell imaging of triple-negative breast cancer cells, it is discovered that both basal and growth-factor stimulated activities of protein kinase B (also known as Akt) and extracellular signal-regulated kinase (ERK), two major kinases driving cancer progression, negatively correlate with increasing distance from the ADV-induced bubble both in vitro and in a mouse model. Together, these data demonstrate that local changes in ECM compaction regulate Akt and ERK signaling in breast cancer and support further applications of the novel ARS technology to analyze spatial and temporal effects of ECM mechanics on cell signaling and cancer biology.

Molecular sensors for detection of tumor-stroma crosstalk

In most solid tumors, malignant cells coexist with non-cancerous host tissue comprised of a variety of extracellular matrix components and cell types, notably fibroblasts, immune cells, and endothelial cells. It is becoming increasingly evident that the non-cancerous host tissue, often referred to as the tumor stroma or the tumor microenvironment, wields tremendous influence in the proliferation, survival, and metastatic ability of cancer cells. The tumor stroma has an active biological role in the transmission of signals, such as growth factors and chemokines that activate oncogenic signaling pathways by autocrine and paracrine mechanisms. Moreover, the constituents of the stroma define the mechanical properties and the physical features of solid tumors, which influence cancer progression and response to therapy. Inspired by the emerging importance of tumor-stroma crosstalk and oncogenic physical forces, numerous biosensors, or advanced imaging and analysis techniques have been developed and applied to investigate complex and challenging questions in cancer research. These techniques facilitate measurements and biological readouts at scales ranging from subcellular to tissue-level with unprecedented level of spatial and temporal precision. Here we examine the application of biosensor technology for studying the complex and dynamic multiscale interactions of the tumor-host system.

Proper migration of lymphatic endothelial cells requires survival and guidance cues from arterial mural cells

The migration of lymphatic endothelial cells (LECs) is key for the development of the complex and vast lymphatic vascular network that pervades most tissues in an organism. In zebrafish, arterial intersegmental vessels together with chemokines have been shown to promote lymphatic cell migration from the horizontal myoseptum (HM). We observed that emergence of mural cells around the intersegmental arteries coincides with lymphatic departure from HM which raised the possibility that arterial mural cells promote LEC migration. Our live imaging and cell ablation experiments revealed that LECs migrate slower and fail to establish the lymphatic vascular network in the absence of arterial mural cells. We determined that mural cells are a source for the C-X-C motif chemokine 12 (Cxcl12a and Cxcl12b), vascular endothelial growth factor C (Vegfc) and collagen and calcium-binding EGF domain-containing protein 1 (Ccbe1). We showed that chemokine and growth factor signalling function cooperatively to induce robust LEC migration. Specifically, Vegfc-Vegfr3 signalling, but not chemokines, induces extracellular signal-regulated kinase (ERK) activation in LECs, and has an additional pro-survival role in LECs during the migration. Together, the identification of mural cells as a source for signals that guide LEC migration and survival will be important in the future design for rebuilding lymphatic vessels in disease contexts.

Single cell imaging of ERK and Akt activation dynamics and heterogeneity induced by G protein-coupled receptors

Kinases play key roles in signaling networks that are activated by G-protein-coupled receptors (GPCRs). Kinase activities are generally inferred from cell lysates, hiding cell-to-cell variability. To study the dynamics and heterogeneity of ERK and Akt proteins, we employed high-content biosensor imaging with kinase translocation reporters. The kinases were activated with GPCR ligands. We observed ligand concentration-dependent response kinetics to histamine, α2-adrenergic and S1P receptor stimulation. By using G-protein inhibitors, we observed that Gq mediated the ERK and Akt responses to histamine. In contrast, Gi was necessary for ERK and Akt activation in response to α2-adrenergic receptor activation. ERK and Akt were also strongly activated by S1P, showing high heterogeneity at the single-cell level, especially for ERK. Cluster analysis of time series derived from 68,000 cells obtained under the different conditions revealed several distinct populations of cells that display similar response dynamics. ERK response dynamics to S1P showed high heterogeneity, which was reduced by the inhibition of Gi. To conclude, we have set up an imaging and analysis strategy that reveals substantial cell-to-cell heterogeneity in kinase activity driven by GPCRs.

Summary: High-content biosensor imaging with kinase translocation reporters reveals substantial cell-to-cell heterogeneity in kinase activity driven by G-protein-coupled receptors.

Computational methods for characterizing and learning from heterogeneous cell signaling data

Heterogeneity in cell signaling pathways is increasingly appreciated as a fundamental feature of cell biology and a driver of clinically relevant disease phenotypes. Understanding the causes of heterogeneity, the cellular mechanisms used to control heterogeneity, and the downstream effects of heterogeneity in single cells are all key obstacles for manipulating cellular populations and treating disease. Recent advances in genetic engineering, including multiplexed fluorescent reporters, have provided unprecedented measurements of signaling heterogeneity, but these vast data sets are often difficult to interpret, necessitating the use of computational techniques to extract meaning from the data. Here, we review recent advances in computational methods for extracting meaning from these novel data streams. In particular, we evaluate how machine learning methods related to dimensionality reduction and classification can identify structure in complex, dynamic datasets, simplifying interpretation. We also discuss how mechanistic models can be merged with heterogeneous data to understand the underlying differences between cells in a population. These methods are still being developed, but the work reviewed here offers useful applications of specific analysis techniques that could enable the translation of single-cell signaling data to actionable biological understanding.

Pre-existing Cell States Control Heterogeneity of Both EGFR and CXCR4 Signaling

INTRODUCTION

CXCR4 and epidermal growth factor receptor (EGFR) represent two major families of receptors, G-protein coupled receptors and receptor tyrosine kinases, with central functions in cancer. While utilizing different upstream signaling molecules, both CXCR4 and EGFR activate kinases ERK and Akt, although single-cell activation of these kinases is markedly heterogeneous. One hypothesis regarding the origin of signaling heterogeneity proposes that intercellular variations arise from differences in pre-existing intracellular states set by extrinsic noise. While pre-existing cell states vary among cells, each pre-existing state defines deterministic signaling outputs to downstream effectors. Understanding causes of signaling heterogeneity will inform treatment of cancers with drugs targeting drivers of oncogenic signaling.

METHODS

We built a single-cell computational model to predict Akt and ERK responses to CXCR4- and EGFR-mediated stimulation. We investigated signaling heterogeneity through these receptors and tested model predictions using quantitative, live-cell time-lapse imaging.

RESULTS

We show that the pre-existing cell state predicts single-cell signaling through both CXCR4 and EGFR. Computational modeling reveals that the same set of pre-existing cell states explains signaling heterogeneity through both EGFR and CXCR4 at multiple doses of ligands and in two different breast cancer cell lines. The model also predicts how phosphatidylinositol-3-kinase (PI3K) targeted therapies potentiate ERK signaling in certain breast cancer cells and that low level, combined inhibition of MEK and PI3K ablates potentiated ERK signaling.

CONCLUSIONS

Our data demonstrate that a conserved motif exists for EGFR and CXCR4 signaling and suggest potential clinical utility of the computational model to optimize therapy.

The CXCL12/CXCR4/ACKR3 Axis in the Tumor Microenvironment: Signaling, Crosstalk, and Therapeutic Targeting

Elevated expression of the chemokine receptors CXCR4 and ACKR3 and of their cognate ligand CXCL12 is detected in a wide range of tumors and the tumor microenvironment (TME). Yet, the molecular mechanisms by which the CXCL12/CXCR4/ACKR3 axis contributes to the pathogenesis are complex and not fully understood. To dissect the role of this axis in cancer, we discuss its ability to impinge on canonical and less conventional signaling networks in different cancer cell types; its bidirectional crosstalk, notably with receptor tyrosine kinase (RTK) and other factors present in the TME; and the infiltration of immune cells that supporttumor progression. We discuss current and emerging avenues that target the CXCL12/CXCR4/ACKR3 axis. Coordinately targeting both RTKs and CXCR4/ACKR3 and/or CXCL12 is an attractive approach to consider in multitargeted cancer therapies. In addition, inhibiting infiltrating immune cells or reactivating the immune system along with modulating the CXCL12/CXCR4/ACKR3 axis in the TME has therapeutic promise.

CaliPro: A Calibration Protocol That Utilizes Parameter Density Estimation to Explore Parameter Space and Calibrate Complex Biological Models

Introduction

Mathematical and computational modeling have a long history of uncovering mechanisms and making predictions for biological systems. However, to create a model that can provide relevant quantitative predictions, models must first be calibrated by recapitulating existing biological datasets from that system. Current calibration approaches may not be appropriate for complex biological models because: 1) many attempt to recapitulate only a single aspect of the experimental data (such as a median trend) or 2) Bayesian techniques require specification of parameter priors and likelihoods to experimental data that cannot always be confidently assigned. A new calibration protocol is needed to calibrate complex models when current approaches fall short.

Methods

Herein, we develop CaliPro, an iterative, model-agnostic calibration protocol that utilizes parameter density estimation to refine parameter space and calibrate to temporal biological datasets. An important aspect of CaliPro is the user-defined pass set definition, which specifies how the model might successfully recapitulate experimental data. We define the appropriate settings to use CaliPro.

Results

We illustrate the usefulness of CaliPro through four examples including predator-prey, infectious disease transmission, and immune response models. We show that CaliPro works well for both deterministic, continuous model structures as well as stochastic, discrete models and illustrate that CaliPro can work across diverse calibration goals.

Conclusions

We present CaliPro, a new method for calibrating complex biological models to a range of experimental outcomes. In addition to expediting calibration, CaliPro may be useful in already calibrated parameter spaces to target and isolate specific model behavior for further analysis.

Short-Term Environmental Conditioning Enhances Tumorigenic Potential of Triple-Negative Breast Cancer Cells

Tumor microenvironments expose cancer cells to heterogeneous, dynamic environments by shifting availability of nutrients, growth factors, and metabolites. Cells integrate various inputs to generate cellular memory that determines trajectories of subsequent phenotypes. Here we report that short-term exposure of triple-negative breast cancer cells to growth factors or targeted inhibitors regulates subsequent tumor initiation. Using breast cancer cells with different driver mutations, we conditioned cells lines with various stimuli for 4 hours before implanting these cells as tumor xenografts and quantifying tumor progression by means of bioluminescence imaging. In the orthotopic model, conditioning a low number of cancer cells with fetal bovine serum led to enhancement of tumor-initiating potential, tumor volume, and liver metastases. Epidermal growth factor and the mTORC1 inhibitor ridaforolimus produced similar but relatively reduced effects on tumorigenic potential. These data show that a short-term stimulus increases tumorigenic phenotypes based on cellular memory. Conditioning regimens failed to alter proliferation or adhesion of cancer cells in vitro or kinase signaling through Akt and ERK measured by multiphoton microscopy in vivo, suggesting that other mechanisms enhanced tumorigenesis. Given the dynamic nature of the tumor environment and time-varying concentrations of small-molecule drugs, this work highlights how variable conditions in tumor environments shape tumor formation, metastasis, and response to therapy.

Targeting disseminated estrogen-receptor-positive breast cancer cells in bone marrow

Estrogen receptor-positive (ER+) breast cancer can recur up to 20 years after initial diagnosis. Delayed recurrences arise from disseminated tumors cells (DTCs) in sites such as bone marrow that remain quiescent during endocrine therapy and subsequently proliferate to produce clinically detectable metastases. Identifying therapies that eliminate DTCs and/or effectively target cells transitioning to proliferation promises to reduce risk of recurrence. To tackle this problem, we utilized a 3D co-culture model incorporating ER+ breast cancer cells and bone marrow mesenchymal stem cells to represent DTCs in a bone marrow niche. 3D co-cultures maintained cancer cells in a quiescent, viable state as measured by both single-cell and population-scale imaging. Single-cell imaging methods for metabolism by fluorescence lifetime (FLIM) of NADH and signaling by kinases Akt and ERK revealed that breast cancer cells utilized oxidative phosphorylation and signaling by Akt to a greater extent both in 3D co-cultures and a mouse model of ER+ breast cancer cells in bone marrow. Using our 3D co-culture model, we discovered that combination therapies targeting oxidative phosphorylation via the thioredoxin reductase (TrxR) inhibitor, D9, and the Akt inhibitor, MK-2206, preferentially eliminated breast cancer cells without altering viability of bone marrow stromal cells. Treatment of mice with disseminated ER+ human breast cancer showed that D9 plus MK-2206 blocked formation of new metastases more effectively than tamoxifen. These data establish an integrated experimental system to investigate DTCs in bone marrow and identify combination therapy against metabolic and kinase targets as a promising approach to effectively target these cells and reduce risk of recurrence in breast cancer.

Enhanced mitochondrial fission suppresses signaling and metastasis in triple-negative breast cancer

BACKGROUND

Mitochondrial dynamics underlies malignant transformation, cancer progression, and response to treatment. Current research presents conflicting evidence for functions of mitochondrial fission and fusion in tumor progression. Here, we investigated how mitochondrial fission and fusion states regulate underlying processes of cancer progression and metastasis in triple-negative breast cancer (TNBC).

METHODS

We enforced mitochondrial fission and fusion states through chemical or genetic approaches and measured migration and invasion of TNBC cells in 2D and 3D in vitro models. We also utilized kinase translocation reporters (KTRs) to identify single cell effects of mitochondrial state on signaling cascades, PI3K/Akt/mTOR and Ras/Raf/MEK/ERK, commonly activated in TNBC. Furthermore, we determined effects of fission and fusion states on metastasis, bone destruction, and signaling in mouse models of breast cancer.

RESULTS

Enforcing mitochondrial fission through chemical or genetic approaches inhibited migration, invasion, and metastasis in TNBC. Breast cancer cells with predominantly fissioned mitochondria exhibited reduced activation of Akt and ERK both in vitro and in mouse models of breast cancer. Treatment with leflunomide, a potent activator of mitochondrial fusion proteins, overcame inhibitory effects of fission on migration, signaling, and metastasis. Mining existing datasets for breast cancer revealed that increased expression of genes associated with mitochondrial fission correlated with improved survival in human breast cancer.

CONCLUSIONS

In TNBC, mitochondrial fission inhibits cellular processes and signaling pathways associated with cancer progression and metastasis. These data suggest that therapies driving mitochondrial fission may benefit patients with breast cancer.

Modulation of CXCR4-Mediated Gi1 Activation by EGF Receptor and GRK2

The CXCL12 chemokine receptor CXCR4 belongs to the GPCR superfamily and is often overexpressed in cancer, being involved in tumor progression and metastasis. How CXCR4 signaling integrates with other relevant oncogenic transduction pathways and the role of GPCR regulatory mechanisms in such contexts are not well-understood. Recent data indicate concurrent upregulation in certain tumors of CXCR4, EGF receptor (EGFR), and G protein-coupled receptor kinase 2 (GRK2), a signaling node functionally linked to both receptor types. We have investigated in a model system the effect of the EGFR and GRK2 status on CXCL12/CXCR4-mediated activation of Gi, the earliest step downstream of receptor activation. We find that overexpressed and activated EGFR reduces CXCR4-mediated Gi1 activation and that GRK2 phosphorylation at tyrosine residues is required to exert its inhibitory actions on CXCR4–Gi stimulation, suggesting a shared path of modulation. Our data point to a role for GRK2 in the crosstalk of the CXCR4 and EGFR signal transduction pathways in pathological contexts characterized by concurrent overactivation of these proteins.