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.

Growth signaling autonomy in circulating tumor cells aids metastatic seeding.

Self-sufficiency (autonomy) in growth signaling, the earliest recognized hallmark of cancer, is fueled by the tumor cell's ability to "secrete-and-sense" growth factors (GFs); this translates into cell survival and proliferation that is self-sustained by autocrine/paracrine secretion. A Golgi-localized circuitry comprised of two GTPase switches has recently been implicated in the orchestration of growth signaling autonomy. Using breast cancer cells that are either endowed or impaired (by gene editing) in their ability to assemble the circuitry for growth signaling autonomy, here we define the transcriptome, proteome, and phenome of such an autonomous state, and unravel its role during cancer progression. We show that autonomy is associated with enhanced molecular programs for stemness, proliferation, and epithelial-mesenchymal plasticity. Autonomy is both necessary and sufficient for anchorage-independent GF-restricted proliferation and resistance to anticancer drugs and is required for metastatic progression. Transcriptomic and proteomic studies show that autonomy is associated, with a surprising degree of specificity, with self-sustained epidermal growth factor receptor (EGFR)/ErbB signaling. Derivation of a gene expression signature for autonomy revealed that growth signaling autonomy is uniquely induced in circulating tumor cells (CTCs), the harshest phase in the life of tumor cells when it is deprived of biologically available epidermal growth factor (EGF). We also show that autonomy in CTCs tracks therapeutic response and prognosticates outcome. These data support a role for growth signaling autonomy in multiple processes essential for the blood-borne dissemination of human breast cancer.

Quantitative MRI reveals heterogeneous impacts of treatment on diseased bone marrow in a mouse model of myelofibrosis.

PURPOSE: Analyzing bone marrow in the hematologic cancer myelofibrosis requires endpoint histology in mouse models and bone marrow biopsies in patients. These methods hinder the ability to monitor therapy over time. Preclinical studies typically begin treatment before mice develop myelofibrosis, unlike patients who begin therapy only after onset of disease. Using clinically relevant, quantitative MRI metrics allowed us to evaluate treatment in mice with established myelofibrosis. METHODS: We used chemical shift-encoded fat imaging, DWI, and magnetization transfer sequences to quantify bone marrow fat, cellularity, and macromolecular components in a mouse model of myelofibrosis. We monitored spleen volume, the established imaging marker for treatment, with anatomic MRI. After confirming bone marrow disease by MRI, we randomized mice to treatment with an approved drug (ruxolitinib or fedratinib) or an investigational agent, navitoclax, for 33 days. We measured the effects of therapy over time with bone marrow and spleen MRI. RESULTS: All treatments produced heterogeneous responses with improvements in bone marrow evident in subsets of individual mice in all treatment groups. Reductions in spleen volume commonly occurred without corresponding improvement in bone marrow. MRI revealed patterns associated with effective and ineffective responses to treatment in bone marrow and identified regional variations in efficacy within a bone. CONCLUSIONS: Quantitative MRI revealed modest, heterogeneous improvements in bone marrow disease when treating mice with established myelofibrosis. These results emphasize the value of bone marrow MRI to assess treatment in preclinical models and the potential to advance clinical trials for patients.

Microfluidic single-cell migration chip reveals insights into the impact of extracellular matrices on cell movement.

Cell migration is a complex process that plays a crucial role in normal physiology and pathologies such as cancer, autoimmune diseases, and mental disorders. Conventional cell migration assays face limitations in tracking a large number of individual migrating cells. To address this challenge, we have developed a high-throughput microfluidic cell migration chip, which seamlessly integrates robotic liquid handling and computer vision to swiftly monitor the movement of 3200 individual cells, providing unparalleled single-cell resolution for discerning distinct behaviors of the fast-moving cell population. This study focuses on the ECM's role in regulating cellular migration, utilizing this cutting-edge microfluidic technology to investigate the impact of ten different ECMs on triple-negative breast cancer cell lines. We found that collagen IV, collagen III, and collagen I coatings were the top enhancers of cell movement. Combining these ECMs increased cell motility, but the effect was sub-additive. Furthermore, we examined 87 compounds and found that while some compounds inhibited migration on all substrates, significantly distinct effects on differently coated substrates were observed, underscoring the importance of considering ECM coating. We also utilized cells expressing a fluorescent actin reporter and observed distinct actin structures in ECM-interacting cells. ScRNA-Seq analysis revealed that ECM coatings induced EMT and enhanced cell migration. Finally, we identified genes that were particularly up-regulated by collagen IV and the selective inhibitors successfully blocked cell migration on collagen IV. Overall, the study provides insights into the impact of various ECMs on cell migration and dynamics of cell movement with implications for developing therapeutic strategies to combat diseases related to cell motility.

Both moderate- and high-intensity exercise training increase intramyocellular lipid droplet abundance and modify myocellular distribution in adults with obesity.

Exercise training modifies lipid metabolism in skeletal muscle, but the effect of exercise training on intramyocellular lipid droplet (LD) abundance, size, and intracellular distribution in adults with obesity remains elusive. This study compared high-intensity interval training (HIIT) with more conventional moderate-intensity continuous training (MICT) on intramyocellular lipid content, as well as LD characteristics (size and number) and abundance within the intramyofibrillar (IMF) and subsarcolemmal (SS) regions of type I and type II skeletal muscle fibers in adults with obesity. Thirty-six adults with obesity [body mass index (BMI) = 33 ± 3 kg/m2] completed 12 wk (4 days/wk) of either HIIT (10 × 1 min, 90% HRmax + 1-min active recovery; n = 19) or MICT (45-min steady-state exercise, 70% HRmax; n = 17), while on a weight-maintaining diet throughout training. Skeletal muscle biopsies were collected from the vastus lateralis before and after training, and intramyocellular lipid content and intracellular LD distribution were measured by immunofluorescence microscopy. Both MICT and HIIT increased total intramyocellular lipid content by more than 50% (P < 0.01), which was attributed to a greater LD number per µm2 in the IMF region of both type I and type II muscle fibers (P < 0.01). Our findings also suggest that LD lipophagy (autophagy-mediated LD degradation) may be transiently upregulated the day after the last exercise training session (P < 0.02 for both MICT and HIIT). In summary, exercise programs for adults with obesity involving either MICT or HIIT increased skeletal muscle LD abundance via a greater number of LDs in the IMF region of the myocyte, thereby providing more lipid in close proximity to the site of energy production during exercise.NEW & NOTEWORTHY In this study, 12 wk of either moderate-intensity continuous training (MICT) or high-intensity interval training (HIIT) enhanced skeletal muscle lipid abundance by increasing lipid droplet number within the intramyofibrillar (IMF) region of muscle. Because the IMF associates with high energy production during muscle contraction, this adaptation may enhance lipid oxidation during exercise. Despite differences in training intensity and energy expenditure between MICT and HIIT, their effects on muscle lipid abundance and metabolism were remarkably similar.

Molecular insights into intrinsic transducer-coupling bias in the CXCR4-CXCR7 system.

Chemokine receptors constitute an important subfamily of G protein-coupled receptors (GPCRs), and they are critically involved in a broad range of immune response mechanisms. Ligand promiscuity among these receptors makes them an interesting target to explore multiple aspects of biased agonism. Here, we comprehensively characterize two chemokine receptors namely, CXCR4 and CXCR7, in terms of their transducer-coupling and downstream signaling upon their stimulation by a common chemokine agonist, CXCL12, and a small molecule agonist, VUF11207. We observe that CXCR7 lacks G-protein-coupling while maintaining robust ßarr recruitment with a major contribution of GRK5/6. On the other hand, CXCR4 displays robust G-protein activation as expected but exhibits significantly reduced ßarr-coupling compared to CXCR7. These two receptors induce distinct ßarr conformations even when activated by the same agonist, and CXCR7, unlike CXCR4, fails to activate ERK1/2 MAP kinase. We also identify a key contribution of a single phosphorylation site in CXCR7 for ßarr recruitment and endosomal localization. Our study provides molecular insights into intrinsic-bias encoded in the CXCR4-CXCR7 system with broad implications for drug discovery.

A Multiomic Analysis Reveals How Breast Cancers Disseminated to the Bone Marrow Acquire Aggressive Phenotypes through Tumor-Stroma Tunnels.

Estrogen receptor-positive (ER+) breast cancer commonly disseminates to bone marrow, where interactions with mesenchymal stromal cells (MSCs) shape disease trajectory. We modeled these interactions with tumor-MSC co-cultures and used an integrated transcriptome-proteome-network- analyses workflow to identify a comprehensive catalog of contact-induced changes. Induced genes and proteins in cancer cells, some borrowed and others tumor-intrinsic, were not recapitulated merely by conditioned media from MSCs. Protein-protein interaction networks revealed the rich connectome between 'borrowed' and 'intrinsic' components. Bioinformatic approaches prioritized one of the 'borrowed' components, CCDC88A /GIV, a multi-modular metastasis-related protein which has recently been implicated in driving one of the hallmarks of cancers, i.e., growth signaling autonomy. MSCs transferred GIV protein to ER+ breast cancer cells (that lack GIV) through tunnelling nanotubes via connexin (Cx)43-facilitated intercellular transport. Reinstating GIV alone in GIV-negative breast cancer cells reproduced ∼20% of both the 'borrowed' and the 'intrinsic' gene induction patterns from contact co-cultures; conferred resistance to anti-estrogen drugs; and enhanced tumor dissemination. Findings provide a multiomic insight into MSC→tumor cell intercellular transport and validate how transport of one such candidate, GIV, from the haves (MSCs) to have-nots (ER+ breast cancer) orchestrates aggressive disease states.

Regulation of DNA damage response by trimeric G-proteins.

Upon sensing DNA double-strand breaks (DSBs), eukaryotic cells either die or repair DSBs via one of the two competing pathways, i.e., non-homologous end-joining (NHEJ) or homologous recombination (HR). We show that cell fate after DSBs hinges on GIV/Girdin, a guanine nucleotide-exchange modulator of heterotrimeric Giα•ßγ protein. GIV suppresses HR by binding and sequestering BRCA1, a key coordinator of multiple steps within the HR pathway, away from DSBs; it does so using a C-terminal motif that binds BRCA1's BRCT-modules via both phospho-dependent and -independent mechanisms. Using another non-overlapping C-terminal motif GIV binds and activates Gi and enhances the "free" Gßγ→PI-3-kinase→Akt pathway, which promotes survival and is known to suppress HR, favor NHEJ. Absence of GIV, or loss of either of its C-terminal motifs enhanced cell death upon genotoxic stress. Because GIV selectively binds other BRCT-containing proteins suggests that G-proteins may fine-tune sensing, repair, and survival after diverse types of DNA damage.

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.

High-Throughput Cellular Heterogeneity Analysis in Cell Migration at the Single-Cell Level.

Cancer cell migration represents an essential step toward metastasis and cancer deaths. However, conventional drug discovery focuses on cytotoxic and growth-inhibiting compounds rather than inhibitors of migration. Drug screening assays generally measure the average response of many cells, masking distinct cell populations that drive metastasis and resist treatments. Here, this work presents a high-throughput microfluidic cell migration platform that coordinates robotic liquid handling and computer vision for rapidly quantifying individual cellular motility. Using this innovative technology, 172 compounds were tested and a surprisingly low correlation between migration and growth inhibition was found. Notably, many compounds were found to inhibit migration of most cells while leaving fast-moving subpopulations unaffected. This work further pinpoints synergistic drug combinations, including Bortezomib and Danirixin, to stop fast-moving cells. To explain the observed cell behaviors, single-cell morphological and molecular analysis were performed. These studies establish a novel technology to identify promising migration inhibitors for cancer treatment and relevant applications.

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.

A lymphatic-absorbed multi-targeted kinase inhibitor for myelofibrosis therapy.

Activation of compensatory signaling nodes in cancer often requires combination therapies that are frequently plagued by dose-limiting toxicities. Intestinal lymphatic drug absorption is seldom explored, although reduced toxicity and sustained drug levels would be anticipated to improve systemic bioavailability. A potent orally bioavailable multi-functional kinase inhibitor (LP-182) is described with intrinsic lymphatic partitioning for the combined targeting of phosphoinositide 3-kinase (PI3K) and mitogen-activated protein kinase (MAPK) signaling pathways without observable toxicity. We demonstrate selectivity and therapeutic efficacy through reduction of downstream kinase activation, amelioration of disease phenotypes, and improved survival in animal models of myelofibrosis. Our further characterization of synthetic and physiochemical properties for small molecule lymphatic uptake will support continued advancements in lymphatropic therapy for altering disease trajectories of a myriad of human disease indications.

Multiparametric MRI to quantify disease and treatment response in mice with myeloproliferative neoplasms.

Histopathology, the standard method to assess BM in hematologic malignancies such as myeloproliferative neoplasms (MPNs), suffers from notable limitations in both research and clinical settings. BM biopsies in patients fail to detect disease heterogeneity, may yield a nondiagnostic sample, and cannot be repeated frequently in clinical oncology. Endpoint histopathology precludes monitoring disease progression and response to therapy in the same mouse over time, missing likely variations among mice. To overcome these shortcomings, we used MRI to measure changes in cellularity, macromolecular constituents, and fat versus hematopoietic cells in BM using diffusion-weighted imaging (DWI), magnetization transfer, and chemical shift-encoded fat imaging. Combining metrics from these imaging parameters revealed dynamic alterations in BM following myeloablative radiation and transplantation. In a mouse MPLW515L BM transplant model of MPN, MRI detected effects of a JAK2 inhibitor, ruxolitinib, within 5 days of initiating treatment and identified differing kinetics of treatment responses in subregions of the tibia. Histopathology validated the MRI results for BM composition and heterogeneity. Anatomic MRI scans also showed reductions in spleen volume during treatment. These findings establish an innovative, clinically translatable MRI approach to quantify spatial and temporal changes in BM in MPN.

The CXCL12/CXCR4/ACKR3 Signaling Axis Regulates PKM2 and Glycolysis.

In response to CXCL12, CXCR4 and ACKR3 both recruit ß-arrestin 2, regulating the assembly of interacting proteins that drive signaling and contribute to the functions of both receptors in cancer and multiple other diseases. A prior proteomics study revealed that ß-arrestin 2 scaffolds pyruvate kinase M2 (PKM2), an enzyme implicated in shifting cells to glycolytic metabolism and poor prognosis in cancer. We hypothesized that CXCL12 signaling regulates PKM2 protein interactions, oligomerization, and glucose metabolism. We used luciferase complementation in cell-based assays and a tumor xenograft model of breast cancer in NSG mice to quantify how CXCR4 and ACKR3 change protein interactions in the ß-arrestin-ERK-PKM2 pathway. We also used mass spectrometry to analyze the effects of CXCL12 on glucose metabolism. CXCL12 signaling through CXCR4 and ACKR3 stimulated protein interactions among ß-arrestin 2, PKM2, ERK2, and each receptor, leading to the dissociation of PKM2 from ß-arrestin 2. The activation of both receptors reduced the oligomerization of PKM2, reflecting a shift from tetramers to dimers or monomers with low enzymatic activity. Mass spectrometry with isotopically labeled glucose showed that CXCL12 signaling increased intermediate metabolites in glycolysis and the pentose phosphate pathway, with ACKR3 mediating greater effects. These data establish how CXCL12 signaling regulates PKM2 and reprograms cellular metabolism.

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.

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.

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.

Single-cell RNA-sequencing of migratory breast cancer cells: discovering genes associated with cancer metastasis.

Considerable evidence suggests breast cancer metastasis arises from cells undergoing epithelial-to-mesenchymal-transition (EMT) and cancer stem-like cells (CSCs). Using a microfluidic device that enriches migratory breast cancer cells with enhanced capacity for tumor formation and metastasis, we identified genes differentially expressed in migratory cells by high-throughput single-cell RNA-sequencing. Migratory cells exhibited overall signatures of EMT and CSCs with variable expression of marker genes, and they retained expression profiles of EMT over time. With single-cell resolution, we discovered intermediate EMT states and distinct epithelial and mesenchymal sub-populations of migratory cells, indicating breast cancer cells can migrate rapidly while retaining an epithelial state. Migratory cells showed differential profiles for regulators of oxidative stress, mitochondrial morphology, and the proteasome, revealing potential vulnerabilities and unexpected consequences of drugs. We also identified novel genes correlated with cell migration and outcomes in breast cancer as potential prognostic biomarkers and therapeutic targets to block migratory cells in metastasis.

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

The chemokine receptor CXCR4 regulates fundamental processes in development, normal physiology, and diseases, including cancer. Small subpopulations of CXCR4-positive cells drive the local invasion and dissemination of malignant cells during metastasis, emphasizing the need to understand the mechanisms controlling responses at the single-cell level to receptor activation by the chemokine ligand CXCL12. Using single-cell imaging, we discovered that short-term cellular memory of changes in environmental conditions tuned CXCR4 signaling to Akt and ERK, two kinases activated by this receptor. Conditioning cells with growth stimuli before CXCL12 exposure increased the number of cells that initiated CXCR4 signaling and the amplitude of Akt and ERK activation. Data-driven, single-cell computational modeling revealed that growth factor conditioning modulated CXCR4-dependent activation of Akt and ERK by decreasing extrinsic noise (preexisting cell-to-cell differences in kinase activity) in PI3K and mTORC1. Modeling established mTORC1 as critical for tuning single-cell responses to CXCL12-CXCR4 signaling. Our single-cell model predicted how combinations of extrinsic noise in PI3K, Ras, and mTORC1 superimposed on different driver mutations in the ERK and/or Akt pathways to bias CXCR4 signaling. Computational experiments correctly predicted that selected kinase inhibitors used for cancer therapy shifted subsets of cells to states that were more permissive to CXCR4 activation, suggesting that such drugs may inadvertently potentiate pro-metastatic CXCR4 signaling. Our work establishes how changing environmental inputs modulate CXCR4 signaling in single cells and provides a framework to optimize the development and use of drugs targeting this signaling pathway.