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.

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.

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.

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. eFNP-59 is an analog of cholesterol that our group validated as an imaging biomarker for cholesterol uptake in preclinical models and initial human studies. In immunocompetent mouse models of TNBC, we found that elevated uptake of exogenous labeled cholesterol analogs functions as a marker for T cell activation. When comparing ICI-responsive and -nonresponsive tumors directly, uptake of fluorescent cholesterol and eFNP-59 increased in T cells from ICI-responsive tumors. We discovered that accumulation of cholesterol by T cells increased in ICI-responding tumors that received anti-PD-1 checkpoint immunotherapy. In patients with TNBC, tumors containing cycling T cells had features of cholesterol uptake and trafficking within those populations. These results suggest that uptake of exogenous cholesterol analogs by tumor-infiltrating T cells allows detection of T cell activation and has potential to assess the success of ICI therapy.

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.

Recurrent and convolutional neural networks for sequential multispectral optoacoustic tomography (MSOT) imaging

Multispectral optoacoustic tomography (MSOT) is a beneficial technique for diagnosing and analyzing biological samples since it provides meticulous details in anatomy and physiology. However, acquiring high through-plane resolution volumetric MSOT is time-consuming. Here, we propose a deep learning model based on hybrid recurrent and convolutional neural networks to generate sequential cross-sectional images for an MSOT system. This system provides three modalities (MSOT, ultrasound, and optoacoustic imaging of a specific exogenous contrast agent) in a single scan. This study used ICG-conjugated nanoworms particles (NWs-ICG) as the contrast agent. Instead of acquiring seven images with a step size of 0.1 mm, we can receive two images with a step size of 0.6 mm as input for the proposed deep learning model. The deep learning model can generate five other images with a step size of 0.1 mm between these two input images meaning we can reduce acquisition time by approximately 71%.

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.

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. To elucidate the role of cancer stemness in resistance of colorectal cancer cells to targeted therapies, we developed spheroid cultures of patient-derived BRAFmut and KRASmut tumor cells and studied resistance mechanisms to inhibition of MAPK pathway through phenotypic and gene and protein expression analysis. We found that treatments enriched the expression of CSC markers CD166, ALDH1A3, CD133, and LGR5 and activated PI3K/Akt pathway in cancer cells. We examined various combination treatments to block these activities and found that a triple combination against BRAF, EGFR, and MEK significantly reduced stemness and activities of oncogenic signaling pathways. This study demonstrates the feasibility of blocking stemness-mediated drug resistance and tumorigenic activities in colorectal cancer.

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. To analyze accumulation of cholesterol by T cells in the immune microenvironment of breast cancer, we leveraged a novel positron emission tomography (PET) radiotracer, FNP-59. FNP-59 is an analog of cholesterol that our group has validated as an imaging biomarker for cholesterol uptake in pre-clinical models and initial human studies. In immunocompetent mouse models of TNBC, we found that elevated uptake of exogenous labeled cholesterol analogs functions as a marker for T cell activation. When comparing immune checkpoint inhibitor (ICI)-responsive EO771 tumors to non-responsive AT-3 tumors, we found significantly higher uptake of a fluorescent cholesterol analog in T cells of the ICI-responsive tumors both in vitro and in vivo. Using the FNP-59 radiotracer, we discovered that accumulation of cholesterol by T cells increased further in ICI-responding tumors that received ant-PD-1 checkpoint immunotherapy. We verified these data by mining single cell sequencing data from patients with TNBC. Patients with tumors containing cycling T cells showed gene expression signatures of cholesterol uptake and trafficking. These results suggest that uptake of exogenous cholesterol analogs by tumor-infiltrating T cells predict T cell activation and success of ICI therapy.

A hybrid breast cancer/mesenchymal stem cell population enhances chemoresistance and metastasis

Patients with triple-negative breast cancer remain at risk for metastatic disease despite treatment. The acquisition of chemoresistance is a major cause of tumor relapse and death, but the mechanisms are far from understood. We have demonstrated that breast cancer cells (BCCs) can engulf mesenchymal stem/stromal cells (MSCs), leading to enhanced dissemination. Here, we show that clinical samples of primary invasive carcinoma and chemoresistant breast cancer metastasis contain a unique hybrid cancer cell population coexpressing pancytokeratin and the MSC marker fibroblast activation protein-α. We show that hybrid cells form in primary tumors and that they promote breast cancer metastasis and chemoresistance. Using single-cell microfluidics and in vivo models, we found that there are polyploid senescent cells within the hybrid cell population that contribute to metastatic dissemination. Our data reveal that Wnt Family Member 5A (WNT5A) plays a crucial role in supporting the chemoresistance properties of hybrid cells. Furthermore, we identified that WNT5A mediates hybrid cell formation through a phagocytosis-like mechanism that requires BCC-derived IL-6 and MSC-derived C-C Motif Chemokine Ligand 2. These findings reveal hybrid cell formation as a mechanism of chemoresistance and suggest that interrupting this mechanism may be a strategy in overcoming breast cancer drug resistance.

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 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.

Enhanced mitochondrial fission inhibits triple-negative breast cancer cell migration through an ROS-dependent mechanism

Mitochondria produce reactive oxygen species (ROS), which function in signal transduction. Mitochondrial dynamics, encompassing morphological shifts between fission and fusion, can directly impact ROS levels in cancer cells. In this study, we identified an ROS-dependent mechanism for how enhanced mitochondrial fission inhibits triple negative breast cancer (TNBC) cell migration. We found that enforcing mitochondrial fission in TNBC resulted in an increase in intracellular ROS levels and reduced cell migration and the formation of actin-rich migratory structures. Consistent with mitochondrial fission, increasing ROS levels in cells inhibited cell migration. Conversely, reducing ROS levels with either a global or mitochondrially targeted scavenger overcame the inhibitory effects of mitochondrial fission. Mechanistically, we found that the ROS sensitive SHP-1/2 phosphatases partially regulate inhibitory effects of mitochondrial fission on TNBC migration. Overall, our work reveals the inhibitory effects of ROS in TNBC and supports mitochondrial dynamics as a potential therapeutic target for cancer.

Fiber density and matrix stiffness modulate distinct cell migration modes in a 3D stroma mimetic composite hydrogel

The peritumoral stroma is a complex 3D tissue that provides cells with myriad biophysical and biochemical cues. Histologic observations suggest that during metastatic spread of carcinomas, these cues influence transformed epithelial cells, prompting a diversity of migration modes spanning single cell and multicellular phenotypes. Purported consequences of these variations in tumor escape strategies include differential metastatic capability and therapy resistance. Therefore, understanding how cues from the peritumoral stromal microenvironment regulate migration mode has both prognostic and therapeutic value. Here, we utilize a synthetic stromal mimetic in which matrix fiber density and bulk hydrogel mechanics can be orthogonally tuned to investigate the contribution of these two key matrix attributes on MCF10A migration mode phenotypes, epithelial-mesenchymal transition (EMT), and invasive potential. We develop an automated computational image analysis framework to extract migratory phenotypes from fluorescent images and determine 3D migration metrics relevant to metastatic spread. Using this analysis, we find that matrix fiber density and bulk hydrogel mechanics distinctly contribute to a variety of MCF10A migration modes including amoeboid, single mesenchymal, clusters, and strands. We identify combinations of physical and soluble cues that induce a variety of migration modes originating from the same MCF10A spheroid and use these settings to examine a functional consequence of migration mode -resistance to apoptosis. We find that cells migrating as strands are more resistant to staurosporine-induced apoptosis than either disconnected clusters or individual invading cells. Improved models of the peritumoral stromal microenvironment and understanding of the relationships between matrix attributes and cell migration mode can aid ongoing efforts to identify effective cancer therapeutics that address cell plasticity-based therapy resistances. STATEMENT OF SIGNIFICANCE: Stromal extracellular matrix structure dictates both cell homeostasis and activation towards migratory phenotypes. However decoupling the effects of myriad biophysical cues has been difficult to achieve. Here, we encapsulate electrospun fiber segments within an amorphous hydrogel to create a fiber-reinforced hydrogel composite in which fiber density and hydrogel stiffness can be orthogonally tuned. Quantification of 3D cell migration reveal these two parameters uniquely contribute to a diversity of migration phenotypes spanning amoeboid, single mesenchymal, multicellular cluster, and collective strand. By tuning biophysical and biochemical cues to elicit heterogeneous migration phenotypes, we find that collective strands best resist apoptosis. This work establishes a composite approach to modulate fibrous topography and bulk hydrogel mechanics and identified biomaterial parameters to direct distinct 3D cell migration phenotypes.

Bone Marrow Mesenchymal Stem Cells Induce Metabolic Plasticity in Estrogen Receptor-Positive Breast Cancer

Cancer cells reprogram energy metabolism through metabolic plasticity, adapting ATP-generating pathways in response to treatment or microenvironmental changes. Such adaptations enable cancer cells to resist standard therapy. We employed a coculture model of estrogen receptor-positive (ER+) breast cancer and mesenchymal stem cells (MSC) to model interactions of cancer cells with stromal microenvironments. Using single-cell endogenous and engineered biosensors for cellular metabolism, coculture with MSCs increased oxidative phosphorylation, intracellular ATP, and resistance of cancer cells to standard therapies. Cocultured cancer cells had increased MCT4, a lactate transporter, and were sensitive to the MCT1/4 inhibitor syrosingopine. Combining syrosingopine with fulvestrant, a selective estrogen receptor degrading drug, overcame resistance of ER+ breast cancer cells in coculture with MSCs. Treatment with antiestrogenic therapy increased metabolic plasticity and maintained intracellular ATP levels, while MCT1/4 inhibition successfully limited metabolic transitions and decreased ATP levels. Furthermore, MCT1/4 inhibition decreased heterogenous metabolic treatment responses versus antiestrogenic therapy. These data establish MSCs as a mediator of cancer cell metabolic plasticity and suggest metabolic interventions as a promising strategy to treat ER+ breast cancer and overcome resistance to standard clinical therapies.

IMPLICATIONS

This study reveals how MSCs reprogram metabolism of ER+ breast cancer cells and point to MCT4 as potential therapeutic target to overcome resistance to antiestrogen drugs.

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.

Animal Models and Their Role in Imaging-Assisted Co-Clinical Trials

The availability of high-fidelity animal models for oncology research has grown enormously in recent years, enabling preclinical studies relevant to prevention, diagnosis, and treatment of cancer to be undertaken. This has led to increased opportunities to conduct co-clinical trials, which are studies on patients that are carried out parallel to or sequentially with animal models of cancer that mirror the biology of the patients' tumors. Patient-derived xenografts (PDX) and genetically engineered mouse models (GEMM) are considered to be the models that best represent human disease and have high translational value. Notably, one element of co-clinical trials that still needs significant optimization is quantitative imaging. The National Cancer Institute has organized a Co-Clinical Imaging Resource Program (CIRP) network to establish best practices for co-clinical imaging and to optimize translational quantitative imaging methodologies. This overview describes the ten co-clinical trials of investigators from eleven institutions who are currently supported by the CIRP initiative and are members of the Animal Models and Co-clinical Trials (AMCT) Working Group. Each team describes their corresponding clinical trial, type of cancer targeted, rationale for choice of animal models, therapy, and imaging modalities. The strengths and weaknesses of the co-clinical trial design and the challenges encountered are considered. The rich research resources generated by the members of the AMCT Working Group will benefit the broad research community and improve the quality and translational impact of imaging in co-clinical trials.

Repeatability of Quantitative Magnetic Resonance Imaging Biomarkers in the Tibia Bone Marrow of a Murine Myelofibrosis Model

Quantitative MRI biomarkers are sought to replace painful and invasive sequential bone-marrow biopsies routinely used for myelofibrosis (MF) cancer monitoring and treatment assessment. Repeatability of MRI-based quantitative imaging biomarker (QIB) measurements was investigated for apparent diffusion coefficient (ADC), proton density fat fraction (PDFF), and magnetization transfer ratio (MTR) in a JAK2 V617F hematopoietic transplant model of MF. Repeatability coefficients (RCs) were determined for three defined tibia bone-marrow sections (2-9 mm; 10-12 mm; and 12.5-13.5 mm from the knee joint) across 15 diseased mice from 20-37 test-retest pairs. Scans were performed on consecutive days every two weeks for a period of 10 weeks starting 3-4 weeks after transplant. The mean RC with (95% confidence interval (CI)) for these sections, respectively, were for ADC: 0.037 (0.031, 0.050), 0.087 (0.069, 0.116), and 0.030 (0.022, 0.044) μm²/ms; for PDFF: 1.6 (1.3, 2.0), 15.5 (12.5, 20.2), and 25.5 (12.0, 33.0)%; and for MTR: 0.16 (0.14, 0.19), 0.11 (0.09, 0.15), and 0.09 (0.08, 0.15). Change-trend analysis of these QIBs identified a dynamic section within the mid-tibial bone marrow in which confident changes (exceeding RC) could be observed after a four-week interval between scans across all measured MRI-based QIBs. Our results demonstrate the capability to derive quantitative imaging metrics from mouse tibia bone marrow for monitoring significant longitudinal MF changes.

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.

Therapeutic Targeting of Cancer Stem Cells Prevents Resistance of Colorectal Cancer Cells to MEK Inhibition

Drug resistance is a leading cause for the failure of cancer treatments. Plasticity of cancer cells to acquire stem cell-like properties enables them to escape drug toxicity through different adaptive mechanisms. Eliminating cancer stem cells (CSCs) can potentially improve treatment outcomes for patients. To determine the role of CSCs in resistance of colorectal cancer cells to targeted therapies and identify treatment strategies, we treated spheroids of BRAFmut and KRASmut colorectal cancer cells with inhibitors of the mitogen-activated protein kinase pathway and studied resistance mechanisms through gene and protein expression analyses. We found that treatments activated several oncogenic pathways and expression of CSC markers CD166 and ALDH1A3. We identified a specific combination treatment using trametinib and mithramycin A to simultaneously inhibit the CSC phenotype and activities of several pathways in cancer cells. This study demonstrates the feasibility of therapeutic targeting of CSCs as a strategy to block tumorigenic activities of cancer cells.

Multi-parametric 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 MPL^W515L 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.

Effects of iron modulation on mesenchymal stem cell-induced drug resistance in estrogen receptor-positive breast cancer

Patients with estrogen receptor-positive (ER+) breast cancer, the most common subtype, remain at risk for lethal metastatic disease years after diagnosis. Recurrence arises partly because tumor cells in bone marrow become resistant to estrogen-targeted therapy. Here, we utilized a co-culture model of bone marrow mesenchymal stem cells (MSCs) and ER+ breast cancer cells to recapitulate interactions of cancer cells in bone marrow niches. ER+ breast cancer cells in direct contact with MSCs acquire cancer stem-like (CSC) phenotypes with increased resistance to standard antiestrogenic drugs. We confirmed that co-culture with MSCs increased labile iron in breast cancer cells, a phenotype associated with CSCs and disease progression. Clinically approved iron chelators and in-house lysosomal iron-targeting compounds restored sensitivity to antiestrogenic therapy. These findings establish iron modulation as a mechanism to reverse MSC-induced drug resistance and suggest iron modulation in combination with estrogen-targeted therapy as a promising, translatable strategy to treat ER+ breast cancer.

Abstract 3936: Orally bioavailable 'lymphatropic' kinase inhibitors

Cancer signaling pathways can readily adapt to evade therapy through intrinsic resistance or compensatory mechanisms driving a resistant state. The prominence of oncogenic kinase signaling in a multitude of cancer types has inspired development of molecularly targeted drugs, facilitating combination treatment strategies designed to overcome adaptations such as signaling crosstalk and activation of downstream effectors. Treatments using inhibitor combinations, however, remain a challenge as clinical trials have been fraught with dose-limiting toxicities. Avoidance of hepatic first-pass metabolism by transport and sequestration into mesenteric gastrointestinal lymphatic vessels may improve drug exposure and reduce dose-limiting toxicities often observed in combination therapy studies. Despite potential advantages, lymphatically directed kinase inhibitors have remained unexplored due in part to limited understanding of the physicochemical properties required for lymphatic uptake of small molecules. We demonstrate a first-in-class series of orally bioavailable small molecule kinase inhibitors which are intrinsically ‘lymphatropic’, undergoing lymphatic absorption to achieve sustained circulatory drug levels and therapeutic benefit, with no observable toxicity. Single agent multifunctional inhibitors of high-value targets (MEK/PI3K, MEK/PI3K/mTOR, & MEK/mTOR) were designed and synthesized. Compounds had unique physiochemical properties, demonstrating high lymphatic uptake in a mesenteric lymphatic vessel cannulation model and in isolated lymph nodes extracts. Pharmacokinetic studies in mice following oral administration revealed that sustained plasma blood levels were achieved within the therapeutic window for up to 24 hours. Oral bioavailability in mice was found to be 80-85% of drug administered and was constant over a single-dose range study (100 to 1,000 mg/kg). On-target in vitro and in vivo inhibition of activated MEK and PI3K was also demonstrated, revealing high potency of both the parent molecule and therapeutically active metabolites. Together, these studies revealed that lymphatic sequestration of orally dosed compounds serves to provide a reservoir that circumvents pharmacotoxicity through controlled physiological drug release into the systemic circulation and avoidance of first-pass hepatic metabolism. This platform provides a template for further development of additional lymphatropic small molecule inhibitors presenting opportunities in which multi-targeted cancer treatment options can now be evaluated. Exciting new therapeutic prospects offered by lymphatropic agent development is anticipated to transform treatment options for a wide variety of cancer types such as metastasis and lymphoma along with a myriad of other diseases including autoimmune disorders.

Citation Format: Brian D. Ross, Youngsoon Jang, Amanda Welton, Christopher A. Bonham, Kevin Heist, Lucas McDonald, Gary D. Luker, Thomas L. Chenevert, Marcian Van Dort. Orally bioavailable 'lymphatropic' kinase inhibitors [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 3936.

Abstract 6366: A novel small molecule inhibitor of MAPK and PI3K ameliorates disease phenotypes in myelofibrosis

Myelofibrosis is a myeloproliferative neoplasm (MPN) caused primarily by mutations in hematopoietic stem and progenitor cells (HSPCs) that activate Janus kinase 2 (JAK2). Central roles for JAK2 signaling in myelofibrosis (MF) have been established, leading to marked extramedullary hematopoiesis, splenomegaly, and bone marrow fibrosis, but the use of JAK inhibitors has shown limited ability to produce durable remissions in most patient populations. Bypass or resistance mechanisms to JAK inhibition have been linked to concomitant activation of compensatory phosphoinositide 3-kinase (PI3K) and mitogen-activated protein kinase (MAPK) signaling pathways, and while genetic and functional studies have not fully defined the mechanisms for transformation and maintenance of the proliferative state in MF, targeting multiple signaling pathways will be required to alter the disease course and improve therapeutic outcomes. Treatments using kinase inhibitor combinations remain a challenge clinically, and trials have struggled to create positive balance between gains in survival, therapeutic efficacy, and dose-limiting toxicity. A multi-functional kinase inhibitor was developed to deliver consistent and synergistic dosing ratios against multiple targets simultaneously, thereby blocking compensatory oncogenic signaling pathways while minimizing the prospect for adverse effects. Using synthetic medicinal chemistry, we present a potent and selective, orally bioavailable, single-molecule multi-targeted kinase inhibitor (LP-182) against MAPK and PI3K/mTOR signaling pathways. We demonstrate selectivity and therapeutic efficacy through in vitro screening of kinome inhibition, reduction of cell growth and downstream kinase activation, renormalization of immune cell populations, amelioration of splenomegaly and bone marrow fibrosis, and improved survival in the myeloproliferative leukemia oncogene (MPLW515L) mouse model of myelofibrosis. Furthermore, treatment with LP-182 was well tolerated showing no observable pharmacotoxicity, and combination with the JAK inhibitor Ruxolitinib also showed ~35% reduction in spleen size as compared to either treatment alone with a ~60% spleen volume reduction compared to vehicle treatment, in the JAK2+/V617F mutant mouse model. Overall, these data suggest that in vivo bioavailability and distribution of LP-182 to secondary lymphoid tissues attenuates MAPK and PI3K signaling to alleviate disease phenotypes in animal models of MF. Simultaneous targeting of both MAPK and PI3K pathways with LP-182 alone or in combination with JAK inhibition provides the potential for significant new opportunities to improve the clinical outcome of MF patients.

Citation Format: Christopher A. Bonham, Youngsoon Jang, Kevin Heist, Amanda Welton, Tanner Robison, Kathryn E. Luker, Gary D. Luker, Winston Y. Lee, Thomas L. Chenevert, Marcian Van Dort, Brian D. Ross. A novel small molecule inhibitor of MAPK and PI3K ameliorates disease phenotypes in myelofibrosis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 6366.

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.

Quantum Light-Enhanced Two-Photon Imaging of Breast Cancer Cells

Correct biological interpretation from cell imaging can be achieved only if the observed phenomena proceed with negligible perturbation from the imaging system. Herein, we demonstrate microscopic images of breast cancer cells created by the fluorescence selectively excited in the process of entangled two-photon absorption in a scanning microscope at an excitation intensity orders of magnitude lower than that used for classical two-photon microscopy. Quantum enhanced entangled two-photon microscopy has shown cell imaging capabilities at an unprecedented low excitation intensity of ∼3.6 × 10⁷ photons/s, which is a million times lower than the excitation level for the classical two-photon fluorescence image obtained in the same microscope. The extremely low light probe intensity demonstrated in entangled two-photon microscopy is of critical importance to minimize photobleaching during repetitive imaging and damage to cells in live-cell applications. This technology opens new avenues in cell investigations with light microscopy, such as enhanced selectivity and time-frequency resolution.

Therapeutic Targeting of Stromal-Tumor HGF-cMET Signaling in an Organotypic Triple Negative Breast Tumor Model

The tumor microenvironment (TME) promotes proliferation, drug resistance, and invasiveness of cancer cells. Therapeutic targeting of the TME is an attractive strategy to improve outcomes for patients, particularly in aggressive cancers such as triple negative breast cancer (TNBC) that have a rich stroma and limited targeted therapies. However, lack of preclinical human tumor models for mechanistic understanding of tumor-stromal interactions has been an impediment to identify effective treatments against the TME. To address this need, we developed a three-dimensional (3D) organotypic tumor model to study interactions of patient-derived cancer-associated fibroblasts (CAFs) with TNBC cells and explore potential therapy targets. We found that CAFs predominantly secreted hepatocyte growth factor (HGF) and activated MET receptor tyrosine kinase in TNBC cells. This tumor-stromal interaction promoted invasiveness, epithelial-to-mesenchymal transition, and activities of multiple oncogenic pathways in TNBC cells. Importantly, we established that TNBC cells become resistant to monotherapy and demonstrated a design-driven approach to select drug combinations that effectively inhibit pro-metastatic functions of TNBC cells. Our study also showed that HGF-MET from lung fibroblasts promotes colony formation by TNBC cells, suggesting that blocking HGF-MET signaling potentially could target both primary TNBC tumorigenesis and lung metastasis. Overall, we established the utility of our organotypic tumor model to identify and therapeutically target specific mechanisms of tumor-stromal interactions in TNBC toward the goal of developing targeted therapies against the TME. Implications: Leveraging a state-of-the-art organotypic tumor model, we demonstrated that CAFs-mediated HGF-MET signaling drive tumorigenic activities in TNBC and presents a therapeutic target.

Structural effects of morpholine replacement in ZSTK474 on Class I PI3K isoform inhibition: Development of novel MEK/PI3K bifunctional inhibitors

Established roles for PI3K and MAPK signaling pathways in tumorigenesis has prompted extensive research towards the discovery of small-molecule inhibitors as cancer therapeutics. However, significant compensatory regulation exists between these two signaling cascades, leading to redundancy among survival pathways. Consequently, initial clinical trials aimed at either PI3K or MEK inhibition alone have proven ineffective and highlight the need for development of targeted and innovative therapeutic combination strategies. We designed a series of PI3K inhibitor derivatives wherein a single morpholine group of the PI3K inhibitor ZSTK474 was substituted with a variety of 2-aminoethyl functional groups. Analogs with pendant hydroxyl or methoxy groups maintained low nanomolar inhibition towards PI3Kα, PI3Kγ, and PI3Kδ isoforms in contrast to those with pendant amino groups which were significantly less inhibitory. Synthesis of prototype PI3K/MEK bifunctional inhibitors (6r, 6s) was guided by the structure-activity data, where a MEK-targeting inhibitor was tethered directly via a short PEG linker to the triazine core of the PI3K inhibitor analogs. These compounds (6r, 6s) displayed nanomolar inhibition towards PI3Kα, δ, and MEK (IC₅₀ ∼105-350 nM), and low micromolar inhibition for PI3Kβ and PI3Kγ (IC₅₀ ∼1.5-3.9 μM) in enzymatic inhibition assays. Cell viability assays demonstrated superior anti-proliferative activity for 6s over 6r in three tumor-derived cell lines (A375, D54, SET-2), which correlated with inhibition of downstream AKT and ERK1/2 phosphorylation. Compounds 6r and 6s also demonstrated in vivo tolerability with therapeutic efficacy through reduction of kinase activation and amelioration of disease phenotypes in the JAK2V617F mutant myelofibrosis mouse cancer model. Taken together, these results support further structure optimization of 6r and 6s as promising leads for combination therapy in human cancer as a new class of PI3K/MEK bifunctional inhibitors.

Parametric Response Mapping of FLAIR MRI Provides an Early Indication of Progression Risk in Glioblastoma

RATIONALE AND OBJECTIVES

Glioblastoma image evaluation utilizes Magnetic Resonance Imaging contrast-enhanced, T1-weighted, and noncontrast T2-weighted fluid-attenuated inversion recovery (FLAIR) acquisitions. Disease progression assessment relies on changes in tumor diameter, which correlate poorly with survival. To improve treatment monitoring in glioblastoma, we investigated serial voxel-wise comparison of anatomically-aligned FLAIR signal as an early predictor of GBM progression.

MATERIALS AND METHODS

We analyzed longitudinal normalized FLAIR images (rFLAIR) from 52 subjects using voxel-wise Parametric Response Mapping (PRM) to monitor volume fractions of increased (PRM_rFLAIR+), decreased (PRM_rFLAIR-), or unchanged (PRM_rFLAIR0) rFLAIR intensity. We determined response by rFLAIR between pretreatment and 10 weeks posttreatment. Risk of disease progression in a subset of subjects (N = 26) with stable disease or partial response as defined by Response Assessment in Neuro-Oncology (RANO) criteria was assessed by PRM_rFLAIR between weeks 10 and 20 and continuously until the PRM_rFLAIR+ exceeded a defined threshold. RANO defined criteria were compared with PRM-derived outcomes for tumor progression detection.

RESULTS

Patient stratification for progression-free survival (PFS) and overall survival (OS) was achieved at week 10 using RANO criteria (PFS: p <0.0001; OS: p <0.0001), relative change in FLAIR-hyperintense volume (PFS: p = 0.0011; OS: p <0.0001), and PRM_rFLAIR+ (PFS: p <0.01; OS: p <0.001). PRM_rFLAIR+ also stratified responding patients' progression between weeks 10 and 20 (PFS: p <0.05; OS: p = 0.01) while changes in FLAIR-volume measurements were not predictive. As a continuous evaluation, PRM_rFLAIR+ exceeding 10% stratified patients for PFA after 5.6 months (p<0.0001), while RANO criteria did not stratify patients until 15.4 months (p <0.0001).

CONCLUSION

PRM_rFLAIR may provide an early biomarker of disease progression in glioblastoma.

Heterogeneous microenvironmental stiffness regulates pro-metastatic functions of breast cancer cells

Besides molecular and phenotypic variations observed in cancer cells, intratumoral heterogeneity also occurs in the tumor microenvironment. Correlative stiffness maps of different intratumor locations in breast tumor biopsies show that stiffness increases from core to periphery. However, how different local ECM stiffness regulates key functions of cancer cells in tumor progression remains unclear. Although increased tissue stiffness is an established driver of breast cancer progression, conclusions from 2D cultures do not correspond with newer data from cancer cells in 3D environments. Many past studies of breast cancer in 3D culture fail to recapitulate the stiffness of a real breast tumor or the various local stiffnesses present in a tumor microenvironment. In this study, we developed a series of collagen/alginate hybrid hydrogels with adjustable stiffness to match the core, middle, and peripheral zones of a breast tumor. We used this hydrogel system to investigate effects of different local stiffness on morphology, proliferation, and migration of breast cancer cells. RNA sequencing of cells in hydrogels with different stiffness revealed changes in multiple cellular processes underlying cancer progression, including angiogenesis and metabolism. We discovered that tumor cells in a soft environment enriched YAP1 and AP1 signaling related genes, whereas tumor cells in a stiff environment became more pro-angiogenic by upregulating fibronectin 1 (FN1) and matrix metalloproteinase 9 (MMP9) expression. This systematic study defines how the range of environmental stiffnesses present in a breast tumor regulates cancer cells, providing new insights into tumorigenesis and disease progression at the tumor-stroma interface. STATEMENT OF SIGNIFICANCE: Applied a well-defined hybrid hydrogel system to mimic the tumor microenvironment with heterogeneous local stiffness. Breast cancer cells tended to proliferate in soft core environment while migrate in stiff peripheral environment. Breast cancer cells shift from glycolysis to OXPHOS and fatty acid metabolism responding to stiff matrix microenvironment. The transcriptomic profile of breast cancer cells altered due to microenvironmental stiffness changes.

Co-Clinical Imaging Resource Program (CIRP): Bridging the Translational Divide to Advance Precision Medicine

The National Institutes of Health’s (National Cancer Institute) precision medicine initiative emphasizes the biological and molecular bases for cancer prevention and treatment. Importantly, it addresses the need for consistency in preclinical and clinical research. To overcome the translational gap in cancer treatment and prevention, the cancer research community has been transitioning toward using animal models that more fatefully recapitulate human tumor biology. There is a growing need to develop best practices in translational research, including imaging research, to better inform therapeutic choices and decision-making. Therefore, the National Cancer Institute has recently launched the Co-Clinical Imaging Research Resource Program (CIRP). Its overarching mission is to advance the practice of precision medicine by establishing consensus-based best practices for co-clinical imaging research by developing optimized state-of-the-art translational quantitative imaging methodologies to enable disease detection, risk stratification, and assessment/prediction of response to therapy. In this communication, we discuss our involvement in the CIRP, detailing key considerations including animal model selection, co-clinical study design, need for standardization of co-clinical instruments, and harmonization of preclinical and clinical quantitative imaging pipelines. An underlying emphasis in the program is to develop best practices toward reproducible, repeatable, and precise quantitative imaging biomarkers for use in translational cancer imaging and therapy. We will conclude with our thoughts on informatics needs to enable collaborative and open science research to advance precision medicine.

Regulation of DNA damage response by trimeric G-protein Signaling.. [DOI: 10.1101/2021.07.21.452842] [Citation(s) in RCA: 0] [Impact Index Per Article: 0]

Upon sensing DNA double-strand breaks (DSBs), eukaryotic cells either die or repair DSBs via one of two competing pathways, i.e., non-homologous end-joining (NHEJ) or homologous recombination (HR). We show that cell fate after DNA damage hinges on the guanine nucleotide-exchange modulator of heterotrimeric G-protein, Giα•βγ, GIV/Girdin. 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. GIV promotes NHEJ, and binds and activates Gi and enhances the ‘free’ Gβγ→PI-3-kinase→Akt pathway, thus revealing the enigmatic origin of prosurvival Akt signals during dsDNA repair. Absence of GIV, or the loss of either of its two functions impaired DNA repair, and induced cell death when challenged with numerous cytotoxic agents. That GIV selectively binds few other BRCT-containing proteins suggests convergent signaling such that heterotrimeric G-proteins may finetune sensing, repair, and outcome after DNA damage.

GRAPHIC ABSTRACT

HIGHLIGHTS

Non-receptor G protein modulator, GIV/Girdin binds BRCA1

Binding occurs in both canonical and non-canonical modes

GIV sequesters BRCA1 away from dsDNA breaks, suppresses HR

Activation of Gi by GIV enhances Akt signals, favors NHEJ

IN BRIEF

In this work, the authors show that heterotrimeric G protein signaling that is triggered by non-receptor GEF, GIV/Girdin, in response to double-stranded DNA breaks is critical for decisive signaling events which favor non-homologous end-joining (NHEJ) and inhibit homologous recombination (HR).

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.