Fat Fraction MRI for Longitudinal Assessment of Bone Marrow Heterogeneity in a Mouse Model of Myelofibrosis.

Background/objectives: Myelofibrosis (MF) is a myeloproliferative neoplasm characterized by the replacement of healthy bone marrow (BM) with malignant and fibrotic tissue. In a healthy state, bone marrow is composed of approximately 60-70% fat cells, which are replaced as disease progresses. Proton density fat fraction (PDFF), a non-invasive and quantitative MRI metric, enables analysis of BM architecture by measuring the percentage of fat versus cells in the environment.

Substrate stiffness regulates triple-negative breast cancer signaling through CXCR4 receptor dynamics.

Biophysical properties of the extracellular matrix (ECM), such as mechanical stiffness, directly regulate behaviors of cancer cells linked to cancer initiation and progression. Cells sense and respond to ECM stiffness in the context of dynamic changes in biochemical inputs, such as growth factors and chemokines. While commonly studied as isolated inputs, mechanisms by which combined effects of mechanical stiffness and biochemical factors affect functions of cancer cells remain poorly defined.

A deep learning aided bone marrow segmentation of quantitative fat MRI for myelofibrosis patients.

Purpose: To automate bone marrow segmentation within pelvic bones in quantitative fat MRI of myelofibrosis (MF) patients using deep-learning (DL) U-Net models.

Methods: Automated segmentation of bone marrow (BM) was evaluated for four U-Net models: 2D U-Net, 2D attention U-Net (2D A-U-Net), 3D U-Net and 3D attention U-Net (3D A-U-Net). An experienced annotator performed the delineation on in-phase (IP) pelvic MRI slices to mark the boundaries of BM regions within two pelvic bones: proximal femur and posterior ilium.

Substrate stiffness regulates triple-negative breast cancer signaling through CXCR4 receptor dynamics.

Biophysical properties of the extracellular matrix (ECM), such as mechanical stiffness, directly regulate behaviors of cancer cells linked to cancer initiation and progression. Cells sense and respond to ECM stiffness in the context of dynamic changes in biochemical inputs, such as growth factors and chemokines. While commonly studied as isolated inputs, mechanisms by which combined effects of mechanical stiffness and biochemical factors affect functions of cancer cells remain poorly defined.

Targeting CAFs-Mediated Stromal Signaling in a Patient-Derived Organotypic Colorectal Tumor Model.

Colorectal cancer, a significant cause of cancer-related mortality, often exhibits drug resistance, highlighting the need for improved tumor models to advance personalized drug testing and precision therapy. We generated organoids from primary colorectal cancer cells cultured through the conditional reprogramming technique, establishing a framework to perform short-term drug testing studies on patient-derived cells. To model interactions with stromal cells in the tumor microenvironment, we combined cancer cell organoids with carcinoma-associated fibroblasts, a cell type implicated in disease progression and drug resistance.

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.

Light-Triggered Protease-Mediated Release of Actin-Bound Cargo from Synthetic Cells.

Synthetic cells offer a versatile platform for addressing biomedical and environmental challenges, due to their modular design and capability to mimic cellular processes such as biosensing, intercellular communication, and metabolism. Constructing synthetic cells capable of stimuli-responsive secretion is vital for applications in targeted drug delivery and biosensor development. Previous attempts at engineering secretion for synthetic cells have been confined to non-specific cargo release via membrane pores, limiting the spatiotemporal precision and specificity necessary for selective secretion.

Genipin-crosslinked double PLL membranes overcome the strength-diffusion trade-off in cell encapsulation without compromising biocompatibility.

Cell microencapsulation technologies allow non-autologous implantation of therapeutic cells for sustained drug delivery purposes. The perm-selective membrane of these systems provides resistance to rupture, stablishes the upper molecular weight limit in bidirectional diffusion of molecules, and affects biocompatibility. Thus, despite being a decisive factor to succeed in terms of biosafety and therapeutic efficacy, little progress has been made in its optimization so far.

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.

Breast cancers that disseminate to bone marrow acquire aggressive phenotypes through CX43-related 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. Conditioned media from MSCs failed to recapitulate genes and proteins, some borrowed and others tumor-intrinsic, induced in cancer cells by direct contact.

Light-triggered protease-mediated release of actin-bound cargo from synthetic cells.

Synthetic cells offer a versatile platform for addressing biomedical and environmental challenges, due to their modular design and capability to mimic cellular processes such as biosensing, intercellular communication, and metabolism. Constructing synthetic cells capable of stimuli-responsive secretion is vital for applications in targeted drug delivery and biosensor development. Previous attempts at engineering secretion for synthetic cells have been confined to non-specific cargo release via membrane pores, limiting the spatiotemporal precision and specificity necessary for selective secretion.

Bioprinted, spatially defined breast tumor microenvironment models of intratumoral heterogeneity and drug resistance.

Cellular, extracellular matrix (ECM), and spatial heterogeneity of tumor microenvironments (TMEs) regulate disease progression and treatment efficacy. Developing in vitro models that recapitulate the TME promises to accelerate studies of tumor biology and identify new targets for therapy. Here, we used extrusion-based, multi-nozzle 3D bioprinting to spatially pattern triple-negative MDA-MB-231 breast cancer cells, endothelial cells (ECs), and human mammary cancer-associated fibroblasts (HMCAFs) with biomimetic ECM inks.

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.

Evaluating immunotherapeutic outcomes in triple-negative breast cancer with a cholesterol radiotracer in mice.

Evaluating the response to immune checkpoint inhibitors (ICIs) remains an unmet challenge in triple-negative breast cancer (TNBC). The requirement for cholesterol in the activation and function of T cells led us to hypothesize that quantifying cellular accumulation of this molecule could distinguish successful from ineffective checkpoint immunotherapy. To analyze accumulation of cholesterol by T cells in the immune microenvironment of breast cancer, we leveraged the PET radiotracer, eFNP-59.

Integrating inverse reinforcement learning into data-driven mechanistic computational models: a novel paradigm to decode cancer cell heterogeneity.

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.

Interlinked switch circuits of biological intelligence.

Eukaryotic cells learn and adapt via unknown network architectures. Recent work demonstrated a circuit of two GTPases used by cells to overcome growth factor scarcity, encouraging our view that artificial and biological intelligence share strikingly similar design principles and that cells function as deep reinforcement learning (RL) agents in uncertain environments.

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.

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.

Predicting efficacy of immunotherapy in mice with triple negative breast cancer using a cholesterol PET radiotracer.

Predicting the response to cancer immunotherapy remains an unmet challenge in triple-negative breast cancer (TNBC) and other malignancies. T cells, the major target of current checkpoint inhibitor immunotherapies, accumulate cholesterol during activation to support proliferation and signaling. The requirement of cholesterol for anti-tumor functions of T cells led us to hypothesize that quantifying cellular accumulation of this molecule could distinguish successful from ineffective checkpoint immunotherapy.

Inhibiting BRAF/EGFR/MEK suppresses cancer stemness and drug resistance of primary colorectal cancer cells.

Drug resistance is a major barrier against successful treatments of cancer patients. Gain of stemness under drug pressure is a major mechanism that renders treatments ineffective. Identifying approaches to target cancer stem cells (CSCs) is expected to improve treatment outcomes 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.