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.

Cancer metastasis, which requires migration of cancer cells away from the primary tumor, is responsible for approximately 65% percent of cancer-related deaths. Therefore, targeting signaling pathways that drive cancer cell migration or proliferation is a common therapeutic approach. Cell migration is commonly studied using experimental approaches which track cells or cell monolayers as they evolve over time. Computational modeling can then be used to fit partial differential equation (PDE) models to the data, providing mechanistic insights underlying the observed cell motion, including the contribution of various cellular behaviors such as random motion, directed motion, and cell division. A popular experimental technique, the scratch assay, measures the migration and proliferation-driven cell closure of a scratch in a confluent cell monolayer. However, these assays do not disambiguate between different drivers of scratch closure (for instance between cell proliferation and migration to open space). To improve analysis of this technique, we combine scratch assays, video microscopy, and PDE inference to gain quantitative insight to mechanisms of cell migration and proliferation. We capture the evolution of cell density fields over time using live-cell microscopy and automated image processing. Our PDE inference methods involve the use of weak form-based system identification techniques for cell density dynamics modeled with advection-diffusion-reaction systems. We then compare our method with recent modeling work, finding that our model discovery tool automatically identifies similar models including reaction and diffusion terms from a larger set of bases. We demonstrate the application of this framework on 2-dimensional scratch assays subject to the inhibiting effect of trametinib on wound closure and characterize the results in the context of the quantified uncertainty in our inference approach. Our integrated experimental and computational pipeline can be used to rapidly identify and refine models of cell migration in a variety of contexts, enabling the quantitative measurement of the effect of drugs and other perturbations on cell migration and proliferation with uncertainty accounted for.

Cellular heterogeneity is a ubiquitous aspect of biology and a major obstacle to successful cancer treatment. Several techniques have emerged to quantify heterogeneity in live cells along axes including cellular migration, morphology, growth, and signaling. Crucially, these studies reveal that cellular heterogeneity is not a result of randomness or a failure in cellular control systems, but instead is a predictable aspect of multicellular systems. We hypothesize that individual cells in complex tissues can behave as reward-maximizing agents and that differences in reward perception can explain heterogeneity. In this perspective, we introduce inverse reinforcement learning as a novel approach for analyzing cellular heterogeneity. We briefly detail experimental approaches for measuring cellular heterogeneity over time and how these experiments can generate datasets consisting of cellular states and actions. Next, we show how inverse reinforcement learning can be applied to these datasets to infer how individual cells choose different actions based on heterogeneous states. Finally, we introduce potential applications of inverse reinforcement learning to three cell biology problems. Overall, we expect inverse reinforcement learning to reveal why cells behave heterogeneously and enable identification of novel treatments based on this new understanding.

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.

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. Conditioned media from MSCs failed to recapitulate genes and proteins, some borrowed and others tumor-intrinsic, induced in cancer cells by direct contact. Protein-protein interaction networks revealed the rich connectome between 'borrowed' and 'intrinsic' components. Bioinformatics prioritized one of the 'borrowed' components, CCDC88A /GIV, a multi-modular metastasis-related protein that has recently been implicated in driving a hallmark of cancer, 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.

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.

AIM:To examine factors underlying why most, but not all, adults with obesity exhibit impaired insulin-mediated glucose uptake, we compared: (1) adipose tissue fatty acid (FA) release, (2) skeletal muscle lipid droplet (LD) characteristics, and (3) insulin signalling events, in skeletal muscle of adults with obesity with relatively high versus low insulin-mediated glucose uptake. METHODS:Seventeen adults with obesity (BMI: 36 ± 3 kg/m2) completed a 2 h hyperinsulinemic-euglycemic clamp with stable isotope tracer infusions to measure glucose rate of disappearance (glucose Rd) and FA rate of appearance (FA Ra). Skeletal muscle biopsies were collected at baseline and 30 min into the insulin infusion. Participants were stratified into HIGH (n = 7) and LOW (n = 10) insulin sensitivity cohorts by their glucose Rd during the hyperinsulinemic clamp (LOW< 400; HIGH >550 nmol/kgFFM/min/[μU/mL]). RESULTS:Insulin-mediated suppression of FA Ra was lower in LOW compared with HIGH (p < 0.01). In skeletal muscle, total intramyocellular lipid content did not differ between cohorts. However, the size of LDs in the subsarcolemmal region (SS) of type II muscle fibres was larger in LOW compared with HIGH (p = 0.01). Additionally, insulin receptor-β (IRβ) interactions with regulatory proteins CD36 and Fyn were lower in LOW versus HIGH (p < 0.01), which aligned with attenuated insulin-mediated Tyr phosphorylation of IRβ and downstream insulin-signalling proteins in LOW. CONCLUSION:Collectively, reduced ability for insulin to suppress FA mobilization, with accompanying modifications in intramyocellular LD size and distribution, and diminished IRβ interaction with key regulatory proteins may be key contributors to impaired insulin-mediated glucose uptake commonly found in adults with obesity.

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.

ABSTRACT To examine factors underlying why most, but not all adults with obesity exhibit impaired insulin-mediated glucose uptake, we compared: 1) rates of fatty acid (FA) release from adipose tissue, 2) skeletal muscle lipid droplet (LD) characteristics, and 3) insulin signaling events in skeletal muscle collected from cohorts of adults with obesity with “HIGH” versus “LOW” insulin sensitivity for glucose uptake. Seventeen adults with obesity (BMI: 36±3kg/m 2 ) completed a 2h hyperinsulinemic-euglycemic clamp with stable isotope tracer infusions to measure glucose rate of disappearance (glucose Rd) and FA rate of appearance (FA Ra). Skeletal muscle biopsies were collected at baseline and 30min into the insulin infusion. Participants were stratified into HIGH (n=7) and LOW (n=10) insulin sensitivity cohorts by their glucose Rd during the hyperinsulinemic clamp (LOW<400; HIGH>550 nmol/kgFFM/min/[µU/mL]). Insulin-mediated suppression of FA Ra was lower in LOW compared with HIGH (p<0.01). In skeletal muscle, total intramyocellular lipid content did not differ between cohorts. However, the size of LDs in the subsarcolemmal region (SS) of type II muscle fibers was larger in LOW compared with HIGH (p=0.01). Additionally, insulin receptor (IR) interactions with regulatory proteins CD36 and Fyn were lower in LOW versus HIGH (p<0.01), which aligned with attenuated insulin-mediated Tyr phosphorylation of IRβ and downstream insulin-signaling proteins in LOW. Collectively, reduced ability for insulin to suppress FA mobilization, with accompanying modifications in intramyocellular LD size and distribution, and diminished IR interaction with key regulatory proteins may be key contributors to impaired insulin-mediated glucose uptake commonly found in adults with obesity. KEY POINTS Although most adults with obesity exhibit impaired insulin-mediated glucose uptake (insulin resistance), some remain sensitive to insulin. Factors that “protect” adults with obesity from developing resistance to insulin-mediated glucose uptake are poorly understood. Potent suppression of fatty acid (FA) mobilization from adipose tissue by insulin is a strong predictor of whole-body insulin-mediated glucose uptake. Participants with higher sensitivity for insulin-mediated glucose uptake had smaller intramyocellular lipid droplets (LDs) within the subsarcolemmal region of type II skeletal muscle fibers. Novel findings revealed that insulin receptor (IR) interaction with the long-chain fatty acid transport protein, CD36, and the Src-family kinase, Fyn, directly associated with higher rates of glucose uptake under basal and hyperinsulinemic conditions. Together, the findings suggest impaired suppression of FA release from adipose tissue associates with reduced glucose uptake in skeletal muscle due in part to a defect in IR activation by CD36/Fyn and altered subcellular LD characteristics.

Supplemental Figure 5. Eribulin dose ranging study.

Supplemental Figure 6. Mobilization of leukocytes with POL5551.

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.

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•βγ 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" Gβγ→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.

Supplemental Figure 1-2. Supplemental Figure 1: Pharmacology of POL5551; Supplemental Figure 2: Correlation of CXCR4 expression in primary tumor with survival in patients

Supplemental Figure 4. MDA-MB-231 primary tumor weight and liver metastases data.

Supplemental Figure 3. Gaussia luciferase complementation imaging model and scratch migration assay with AMD3100.

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. Cell migration in a microfluidic channel coated with various ECMs.

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 βarr recruitment with a major contribution of GRK5/6. On the other hand, CXCR4 displays robust G-protein activation as expected but exhibits significantly reduced βarr-coupling compared to CXCR7. These two receptors induce distinct βarr 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 βarr recruitment and endosomal localization. Our study provides molecular insights into intrinsic-bias encoded in the CXCR4-CXCR7 system with broad implications for drug discovery.

Supplemental Figure 7. Effect of POL5551 combined with eribulin on hematopoietic cells

Supplemental Table 1-3. Pharmacology of POL5551 and patient characteristics at baseline