Search Results (14)

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. Our objective is to investigate variance in quantitative PDFF-MRI values over time as a marker of disease progression and response to treatment. Methods: We analyzed existing data from three cohorts of mice: two groups with MF that failed to respond to therapy with approved drugs for MF (ruxolitinib, fedratinib), investigational compounds (navitoclax, balixafortide), or vehicle and monitored over time by MRI; the third group consisted of healthy controls imaged at a single time point. Using in-house MATLAB programs, we performed a voxel-wise analysis of PDFF values in lower extremity bone marrow, specifically comparing the variance of each voxel within and among mice. Results: Our findings revealed a significant difference in PDFF values between healthy and diseased BM. With progressive disease non-responsive to therapy, the expansion of hematopoietic cells in BM nearly completely replaced normal fat, as determined by a markedly reduced PDFF and notable reduction in the variance in PDFF values in bone marrow over time. Conclusions: This study validated our hypothesis that the variance in PDFF in BM decreases with disease progression, indicating pathologic expansion of hematopoietic cells. We can conclude that disease progression can be tracked by a decrease in PDFF values. Analyzing variance in PDFF may improve the assessment of disease progression in pre-clinical models and ultimately patients with MF. Full article

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. Full article

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. Full article

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. Full article

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

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. Full article

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

Fluorescence lifetime imaging (FLIM) is a powerful imaging modality used to gather fluorescent reporter data independent of intracellular reporter intensity or imaging depth. We applied this technique to image real-time activation of a reporter for the proteolytic enzyme, caspase-3, in response to apoptotic cell death. This caspase-3 reporter activity provides valuable insight into cancer cell responsiveness to therapy and overall viability at a single-cell scale. Cleavage of a aspartate-glutamate-valine-aspartate (DEVD) linkage sequence alters Förster resonance energy transfer (FRET) within the reporter, affecting its lifetime. Cellular apoptosis was quantified in multiple environments ranging from 2D flat and 3D spheroid cell culture systems to in vivo murine mammary tumor xenografts. We evaluated cell-by-cell apoptotic responses to multiple pharmacological and genetic methods of interest involved in cancer cell death. Within this article, we describe methods for measuring caspase-3 activation at single-cell resolution in various complex environments using FLIM. Full article

Bone constitutes the most common site of breast cancer metastases either at time of presentation or recurrent disease years after seemingly successful therapy. Bone metastases cause substantial morbidity, including life-threatening spinal cord compression and hypercalcemia. Given the high prevalence of patients with breast cancer, health-care costs of bone metastases (>$20,000 per episode) impose a tremendous economic burden on society. To investigate mechanisms of bone metastasis, we developed femoral artery injection of cancer cells as a physiologically relevant model of bone metastasis. Comparing young (∼6 weeks), skeletally immature mice to old (∼6 months) female mice with closed physes (growth plates), we showed significantly greater progression of osteolytic metastases in young animals. Bone destruction increased in the old mice following ovariectomy, emphasizing the pathologic consequences of greater bone turnover and net loss. Despite uniform initial distribution of breast cancer cells throughout the hind limb after femoral artery injection, we observed preferential formation of osteolytic bone metastases in the proximal tibia. Tropism for the proximal tibia arises in part because of TGF-β, a cytokine abundant in both physes of skeletally immature mice and matrix of bone in mice of all ages. We also showed that age-dependent effects on osteolytic bone metastases did not occur in male mice with disseminated breast cancer cells in bone. These studies establish a model system to specifically focus on pathophysiology and treatment of bone metastases and underscore the need to match biologic variables in the model to relevant subsets of patients with breast cancer. Full article

Management of glioblastoma multiforme remains a challenging problem despite recent advances in targeted therapies. Timely assessment of therapeutic agents is hindered by the lack of standard quantitative imaging protocols for determining targeted response. Clinical response assessment for brain tumors is determined by volumetric changes assessed at 10 weeks post-treatment initiation. Further, current clinical criteria fail to use advanced quantitative imaging approaches, such as diffusion and perfusion magnetic resonance imaging. Development of the parametric response mapping (PRM) applied to diffusion-weighted magnetic resonance imaging has provided a sensitive and early biomarker of successful cytotoxic therapy in brain tumors while maintaining a spatial context within the tumor. Although PRM provides an earlier readout than volumetry and sometimes greater sensitivity compared with traditional whole-tumor diffusion statistics, it is not routinely used for patient management; an automated and standardized software for performing the analysis and for the generation of a clinical report document is required for this. We present a semiautomated and seamless workflow for image coregistration, segmentation, and PRM classification of glioblastoma multiforme diffusion-weighted magnetic resonance imaging scans. The software solution can be integrated using local hardware or performed remotely in the cloud while providing connectivity to existing picture archive and communication systems. This is an important step toward implementing PRM analysis of solid tumors in routine clinical practice. Full article

Malignant cells from breast cancer, as well as other common cancers such as prostate and melanoma, may persist in bone marrow as quiescent, nondividing cells that remain viable for years or even decades before resuming proliferation to cause recurrent disease. This phenomenon, referred to clinically as tumor dormancy, poses tremendous challenges to curing patients with breast cancer. Quiescent tumor cells resist chemotherapy drugs that predominantly target proliferating cells, limiting success of neoadjuvant and adjuvant therapies. We recently developed a 3-dimensional spheroid model of quiescent breast cancer cells in bone marrow for mechanistic and drug testing studies. We combined this model with optical imaging methods for label-free detection of cells, preferentially using glycolysis versus oxidative metabolism to investigate the metabolic state of co-culture spheroids with different bone marrow stromal and breast cancer cells. Through imaging and biochemical assays, we identified different metabolic states of bone marrow stromal cells that control metabolic status and flexibilities of co-cultured breast cancer cells. We tested metabolic stresses and targeted inhibition of specific metabolic pathways to identify approaches to preferentially eliminate quiescent breast cancer cells from bone marrow environments. These studies establish an integrated imaging approach to analyze metabolism in complex tissue environments to identify new metabolically targeted cancer therapies. Full article

Myelofibrosis (MF) is a hematologic neoplasm arising as a primary disease or secondary to other blood malignancies. Both primary and secondary MF develop progressive fibrosis of bone marrow, displacing normal hematopoietic cells to other organs and disrupting normal production of mature blood cells. Activation of JAK2 signaling in hematopoietic stem cells commonly causes MF, and ruxolitinib, a drug targeting this pathway, is the preferred treatment for many patients. However, current measures of disease status in MF do not necessarily predict response to treatment with ruxolitinib or other drugs. Bone marrow biopsies are invasive and prone to sampling error, while measurements of spleen volume only indirectly reflect status of bone marrow. Toward the goal of developing an imaging biomarker for treatment response in MF, we present preliminary results from a prospective clinical study evaluating parametric response mapping (PRM) of quantitative Dixon MRI bone marrow fat fraction maps in four MF patients treated with ruxolitinib. PRM allows voxel-wise identification of temporal changes in quantitative imaging readouts, in this case bone marrow fat. We identified heterogeneous responses of bone marrow fat among patients and within different bone marrow sites in the same patient. Changes in bone marrow fat fraction also were discordant with reductions in spleen volume, the standard imaging metric for treatment response. This study provides initial support for PRM analysis of quantitative MRI of bone marrow fat to monitor therapy in MF, setting the stage for larger studies to further develop and validate this method as a complementary imaging biomarker. Full article

Genetically encoded fluorescence resonance energy transfer (FRET) reporters are powerful tools for analyzing cell signaling and function at single-cell resolution in standard 2D cell cultures, but these reporters rarely have been applied to 3D environments. FRET interactions between donor and acceptor molecules typically are determined by changes in relative fluorescence intensities, but wavelength-dependent differences in light absorption complicate this analysis method in 3D settings. Herein we report fluorescence lifetime imaging microscopy (FLIM) with phasor analysis, a method that displays fluorescence lifetimes on a pixel-wise basis in real time to quantify apoptosis in breast cancer cells stably expressing a genetically encoded FRET reporter. This microscopic imaging technology allowed us to identify treatment-induced apoptosis in single breast cancer cells in environments ranging from 2D cell culture, spheroids with cancer and bone marrow stromal cells, and living mice with orthotopic human breast cancer xenografts. Using this imaging strategy, we showed that combined metabolic therapy targeting glycolysis and glutamine pathways significantly reduced overall breast cancer metabolism and induced apoptosis. We also determined that distinct subpopulations of bone marrow stromal cells control the resistance of breast cancer cells to chemotherapy, suggesting heterogeneity of treatment responses of malignant cells in different bone marrow niches. Overall, this study establishes FLIM with phasor analysis as an imaging tool for apoptosis in cell-based assays and living mice, enabling real-time, cellular-level assessment of treatment efficacy and heterogeneity. Full article

Pathologic vertebral compression fractures (PVCFs) cause significant morbidity in patients with metastatic bone disease. Limitations in existing clinical biomarkers leave clinicians without reliable metrics for predicting PVCF, thus impeding efforts to prevent this severe complication. To establish the feasibility of a new method for defining the risk of a PVCF, we retrospectively analyzed serial computed tomography (CT) scans from 5 breast cancer patients using parametric response mapping (PRM) to quantify dynamic bone miniral density (BMD) changes that preceded an event. Vertebrae segmented from each scan were registered to the same spatial frame and voxel classification was accomplished using a predetermined threshold of change in Hounsfield units (HU), resulting in relative volumes of increased (PRM_HU+), decreased (PRM_HU−), or unchanged (PRM_HU0) attenuation. A total of 7 PVCFs were compared to undiseased vertebrae in each patient serving as controls. A receiver operator curve (ROC) analysis identified optimal imaging times for group stratification. BMD changes were apparent by an elevated PRM_HU+ as early as 1 year before fracture. ROC analysis showed poor performance of PRM_HU− in stratifying PVCFs versus controls. As early as 6 months before PVCF, PRM_HU+ was significantly larger (12.9 ± 11.6%) than control vertebrae (2.3 ± 2.5%), with an area under the curve of 0.918 from an ROC analysis. Mean HU changes were also significant between PVCF (26.8 ± 26.9%) and control (−2.2 ± 22.0%) over the same period. A PRM analysis of BMD changes using standard CT imaging was sensitive for spatially resolving changes that preceded structural failure in these patients. Full article