Search

Background: While estrogen typically promotes the progression of hormone-dependent breast cancer via the activation of estrogen receptor (ER)-α, estrogen-induced suppression of ER+ breast cancer has been clinically observed. Our previous study demonstrated that estrogen increased the percentage of cells expressing IL24, linking to the estrogen-dependent growth inhibition of an ER+ aromatase inhibitor (AI)-resistant tumor (Mori et al. Cancers, 2021). To continue our evaluation, we investigated whether progesterone (P4) and dihydrotestosterone (DHT) would affect the growth of this estrogen-suppressive tumor. Methods: An estrogen-suppressive patient-derived xenograft (PDX) model (named GS3) was established from an AI resistant ER+/HER2– brain metastatic breast cancer. E2 (1mg), P4 (10mg), DHT (12.5mg), or placebo pellets were implanted in mice carrying GS3 for in vivo drug efficacy examination. Beside tumor growth response, immunohistochemistry (IHC) and RNA sequencing of PDX specimens were conducted to decipher molecular changes after each treatment. The single-cell RNAseq analysis was further performed to examine gene expression profiles in individual cells. Results: ERα, ERβ, Progesterone receptor (PR), and androgen receptor (AR) genes in GS3 are wild-type and are not amplified. Measurements of tumor volume showed that E2, E2+P4, and DHT suppressed the growth of GS3. The Tumor growth was not modulated by P4 treatment. IHC indicated that the number of Ki-67+ cells were decreased after E2, E2+P4, and DHT treatments, but were not changed after P4 treatment. PR+ cells appeared after E2 and E2+P4 treatments, and the AR+ cells increased after DHT treatment. Bulk-RNA sequencing indicated that E2 and E2+P4 treatments resulted in comparable gene expression patterns, while those of placebo and P4-treated tumors were similar. GSEA analysis showed that in E2 treatment, the hallmark estrogen response gene sets were upregulated, and the hallmark G2M checkpoint gene set was downregulated. However, in DHT treatment, the hallmark interferon alpha/gamma response gene sets and androgen response gene set were upregulated, and the hallmark TNFA signaling via NFkB gene set was downregulated. Single-cell RNA sequencing analysis of Placebo/E2/DHT samples revealed 9 clusters; cells from E2-treated and DHT-treated tumors were placed in different clusters based on principle component analysis of Highly Variable Genes, although both E2 and DHT treatments resulted in tumor regression. DHT promoted cell cycle arrest, but it did not increase IL24 expression. The hallmark oxidative phosphorylation and androgen response gene sets were upregulated in all clusters from DHT-treated tumors. Trajectory analysis of single cells revealed that three major branches associated with clusters selective to the treatments of placebo, E2, and DHT were separated from a common branch which are consist of G2M phase cells. Conclusions: E2 and DHT were effective suppressor of GS3, but not P4. Based on the results from IHC, bulk-RNAseq, and Single-cell RNAseq, the mechanism of DHT-induced tumor regression is different from that by E2. Our results suggest that DHT/E2 could be treatment options for patients with relapsed ER+ AI-resistance breast cancer. Citation Format: Hitomi Mori, Kohei Saeki, Gregory Chang, Jinhui Wang, Xiwei Wu, Noriko Kanaya, George Somlo, Shiuan Chen. Efficacy of Gonadal steroids on aromatase inhibitor-resistant ER+ breast cancer: Insights from single-cell trajectory analysis of a patient-derived xenograft model [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P3-11-05.

Osteoporosis is the most common disease affecting bones worldwide. Dual x-ray absorptiometry (DXA) is the current reference standard for assessing bone health and, combined with other clinical parameters, provides a good estimation of fracture risk. DXA-based Trabecular Bone Score (TBS) can provide complementary indirect information about bone microarchitecture, which also deteriorates osteoporosis. QCT can provide a 3-D volumetric assessment of bone mineral density (BMD), and FEA of computed tomography (CT) images of bone can provide estimates of bone strength, which have the potential to add value, beyond BMD, for fracture risk assessment. Magnetic resonance imaging (MRI) of bone microarchitecture is an additional promising alternative to the assessment of BMD, and there is evidence that microarchitectural parameters could 1 day have benefits for diagnosing osteoporosis beyond BMD and/or FRAX. Assessment of bone via MRI also provides insight into other bone tissue properties (cortical porosity, marrow fat) that are altered in osteoporosis and that DXA cannot assess. Overall, bone health cannot be characterized solely by one parameter. Current imaging techniques/modalities in combination with advanced image processing hold the potential to provide a comprehensive understanding of the pathologic changes that occur in bone tissue in the setting of osteoporosis and pave the way for new imaging methods to diagnose, monitor, and predict osteoporosis.

BackgroundIntratumor heterogeneity is a hallmark of most solid tumors, including breast cancers. We applied spatial transcriptomics and single-cell RNA-sequencing technologies to profile spatially resolved cell populations within estrogen receptor-positive (ER+) metastatic breast cancers and elucidate their importance in estrogen-dependent tumor growth.MethodsSpatial transcriptomics and single-cell RNA-sequencing were performed on two patient-derived xenografts (PDXs) of “ER-high” metastatic breast cancers with opposite estrogen-mediated growth responses: estrogen-suppressed GS3 (80–100% ER) and estrogen-stimulated SC31 (30–75% ER) models. The analyses included samples treated with and without 17β-estradiol. The findings were validated via scRNA-seq analyses on “ER-low” estrogen-accelerating PDX, GS1 (5% ER). The results from our spatial and single-cell analyses were further supported by the analysis of a publicly available single cell dataset and a protein-based dual immunohistochemical (IHC) evaluation using three important clinical markers [i.e., ER, progesterone receptor (PR), and Ki67]. The translational implication of these results was assessed by clinical outcome analyses on public breast cancer cohorts.ResultsOur novel space-gene-function study revealed a “proliferative” cell population in addition to three major spatially distinct compartments within ER+metastatic breast cancers. These compartments showed functional diversity (i.e., estrogen-responsive, proliferative, hypoxia-induced, and inflammation-related). The “proliferative (MKI67+)” population, not “estrogen-responsive” compartment, was crucial for estrogen-dependent tumor growth, leading to the acquisition of luminal B features. The cells with induction of typical estrogen-responsive genes such asPGRwere not directly linked to estrogen-dependent proliferation. Additionally, the dual IHC analyses demonstrated the distinct contribution of the Ki67+proliferative cells toward estrogen-mediated growth and their response to palbociclib, a CDK4/6 inhibitor. The gene signatures developed from the proliferative, hypoxia-induced, and inflammation-related compartments were significantly correlated with worse clinical outcomes, while patients with the high estrogen-responsive scores showed better prognosis, confirming that the estrogen-responsive compartment would not be directly associated with estrogen-dependent tumor progression.ConclusionsFor the first time, our study elucidated a “proliferative” cell population distinctly distributed in ER+metastatic breast cancers. They contribute differently toward progression of these cancers, and the gene signature in the “proliferative” compartment is an important determinant of luminal cancer subtypes.

Osteoporosis is a bone disease associated with enhanced bone loss, microstructural degeneration, and fracture-risk. Finite element (FE) modeling is used to estimate trabecular bone (Tb) modulus from high-resolution three-dimensional (3-D) imaging modalities including micro-computed tomography (CT), magnetic resonance imaging (MRI), and high-resolution peripheral quantitative CT (HR-pQCT). This paper validates an application of voxel-based continuum finite element analysis (FEA) to predict Tb modulus from clinical CT imaging under a condition similar to in vivo imaging by comparing with measures derived by micro-CT and experimental approaches.Voxel-based continuum FEA methods for CT imaging were implemented using linear and nonlinear models and applied on distal tibial scans under a condition similar to in vivo imaging. First, tibial axis in a CT scan was aligned with the coordinate z-axis at 150 μm isotropic voxels. FEA was applied on an upright cylindrical volume of interests (VOI) with its axis coinciding with the tibial bone axis. Voxel volume, edge, and vertex elements and their connectivity were defined as per the isotropic image grid. A calibration phantom was used to calibrate CT numbers in Hounsfield unit to bone mineral density (BMD) values, which was then converted into calcium hydroxyapatite (CHA) density. Mechanical properties at each voxel volume element was defined using its ash-density defined on CT-derived CHA density. For FEA, the bottom surface of the cylindrical VOI was fixed and a constant displacement was applied along the z-direction at each vertex element on the top surface to simulate a physical axial compressive loading condition. Finally, a Poisson's ratio of 0.3 was applied, and Tb modulus (MPa) was computed as the ratio of average von Mises stress (MPa) of volume elements on the top surface and the applied displacement. FEA parameters including mesh element size, substep number, and different tolerance values were optimized.CT-derived Tb modulus values using continuum FEA showed high linear correlation with the micro-CT-derived reference values (r ∈ [0.87 0.90]) as well as experimentally measured values (r ∈ [0.80 0.87]). Linear correlation of computed modulus with their reference values using continuum FEA with linear modeling was comparable with that obtained by nonlinear modeling. Nonlinear continuum FEA-based modulus values (mean of 1087.2 MPa) showed greater difference from their reference values (mean of 1498.9 MPa using micro-CT-based FEA) as compared with linear continuum methods. High repeat CT scan reproducibility (intra-class correlation [ICC] = 0.98) was observed for computed modulus values using both linear and nonlinear continuum FEA. It was observed that high stress regions coincide with Tb microstructure as fuzzily characterized by BMD values. Distributions of von Mises stress over Tb microstructure and marrow regions were significantly different (p 10Voxel-based continuum FEA offers surrogate measures of Tb modulus from CT imaging under a condition similar to in vivo imaging that alleviates the need for segmentation of Tb and marrow regions, while accounting for bone distribution at the microstructural level. This relaxation of binary segmentation will extend the scope of FEA application to assess mechanical properties of bone microstructure at relatively low-resolution imaging.

Background: Estrogen typically promotes the progression of hormone-dependent breast cancer through activation of estrogen receptor (ER)-α encoded by ESR1. While estrogen-induced tumor suppression in ER+ breast cancer has been clinically observed as an unexpected outcome of aromatase inhibitor (AI)-resistance, the molecular mechanisms have not yet been fully defined. Methods: Characterization of estrogen regulation in the two ER+ breast cancer patient-derived xenograft (PDX) models with opposite responses to estrogen offered us an unprecedented opportunity to assess how 17β-estradiol (E2) modulates ER+ cancer. We succeeded in establishing estrogen-stimulating (SC31) and estrogen-suppressing (GS3) PDX models. In vivo tumor promotion or suppression by estrogen was confirmed through experiments by implanting E2 pellets in mice carrying SC31/GS3, and then single cell analysis was performed using SC31/GS3 tumors. To investigate whether GS3 would change its response to E2, we performed intermittent E2 treatment every 28 days (E2 pellet on/off every 28 days) and whole-genome RNA sequencing using GS3 tumors. Results: SC31 and GS3 behaved oppositely regarding estrogen-mediated tumor growth. Immunohistochemistry indicated that the number of ERα+ cells and Ki-67+ cells were increased in SC31 and decreased in GS3 after E2 treatment, but progesterone receptor+ cells appeared in both SC31 and GS3 after E2 treatment at the protein level. The E2-induced suppression of GS3 involves ERα, not ERβ, which was wild-type and not amplified. Single cell RNA sequencing analysis of these PDXs had revealed that E2 upregulated the expression of estrogen-regulated genes (e.g., PGR and AREG) in both SC31 and GS3. However, E2 treatment induced cell cycle promotion in SC31, while E2 induced cell cycle arrest in GS3. These gene-expression changes occurred in both ESR1+ cells and ESR1- cells, demonstrating for the first time the influence of estrogen on ESR1- cells in ER+breast tumors. This result suggests that 100% ER positivity is not essential for endocrine response. E2 also upregulated a tumor suppressor gene, IL24, only in GS3. More IL24+ cells were ESR1+ and in G1 phase than IL24- cells. Hallmark apoptosis gene sets were upregulated and the hallmark G2M checkpoint gene set was downregulated in IL24+ cells after E2 treatment. After three rounds of intermittent E2 treatment on GS3, an E2 independent growth developed. Approximately 60% of genes in the intermittent E2-treated sample had the same trend as E2-treated samples (mainly ER target genes), in which 40% of the genes behaved similarly to the placebo-treated sample (mainly cell cycle progression genes). Furthermore, lower levels of IL24 were linked to estrogen independence. Conclusions: Estrogen/ERα signaling increases the expression of estrogen-regulated genes, but it can modulate HR+ tumor growth in different manners. While E2 should activate ERα and regulate ESR1+ cells, our findings regarding ESR1- cells were new and suggested crosstalk between ESR1+ cells and ESR1- cells in both estrogen-stimulating and -suppressing ER+ tumors. Furthermore, our studies demonstrate the potential roles of tumor suppressor gene, IL24 in HR+ cancer. Our findings point to the need to identify biomarkers for patients with estrogen-suppressing tumors who can benefit from E2 treatment after AI resistance; measurements of ER and PR expression are insufficient. Expression of IL24 in AI-resistant tumors may be one such indicator for favorable response to E2 therapy. Citation Format: Hitomi Mori, Kohei Saeki, Gregory Chang, Jinhui Wang, Xiwei Wu, Pei-Yin Hsu, Noriko Kanaya, George Somlo, Masafumi Nakamura, Andrea Bild, Shiuan Chen. Estrogen-mediated mechanisms in estrogen receptor-positive breast cancer at the single cell level [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr PD1-04.

Systemic lupus erythematosus (SLE) is a chronic, inflammatory disease with common musculoskeletal manifestations, notably reductions in bone quality. Bone marrow adipose tissue composition and quantity has been previously linked to bone quality and may play a role in SLE pathophysiology but has not been thoroughly studied.To use magnetic resonance spectroscopy (MRS) to investigate bone marrow adipose tissue quantity and composition in proximal femur subregions of untreated SLE patients compared to controls and treated patients.Prospective.A total of 64 female subjects: 28 SLE, 15 glucocorticoid (GC)-treated SLE and 21 matched controls.Stimulated echo acquisition mode (STEAM) sequence at 3 T.MRS was performed at multiple echo times in the femoral neck and trochanter regions and fatty acids (FA) composition was computed.Intergroup comparisons were carried out using ANOVA. A P value 0.05 was considered statistically significant.SLE patients had significantly higher saturated FA compared to controls in both the femoral neck (+0.12) and trochanter (+0.11), significantly lower monounsaturated FA in the trochanter compared to controls (-0.05), and significantly lower polyunsaturated FA in the femoral neck compared to both controls (-0.07) and SLE patients on GC therapy (-0.05).SLE patients have altered proximal femur marrow fat metabolism, which may reflect a manifestation of, or play a role in, the altered inflammatory response of these patients.2 TECHNICAL EFFICACY: Stage 2.

Magnetic resonance fingerprinting (MRF) techniques have been recently described for simultaneous multiparameter cartilage mapping of the knee although investigation of their ability to detect early cartilage degeneration remains limited.To investigate age-dependent changes in knee cartilage TProspective.The study group consisted of 24 healthy asymptomatic human volunteers (15 males with mean age 34.9 ± 14.4 years and 9 females with mean age 44.5 ± 13.1 years).A 3.0 T gradient-echo-based 3D-MRF sequence was used to simultaneously create proton density-weighted images and TMean global cartilage and regional cartilage (lateral femur, lateral tibia, medial femur, medial tibia, and patella) TKruskal-Wallis tests were used to compared cartilage THigher age groups showed higher global and regional cartilage TCartilage T

Introduction Polybrominated diphenyl ethers (PBDEs) are persistent environmental contaminants and associated with breast carcinogenesis. In this study, we examined the effects of PBDEs during the menopausal transition in a 4-vinylcyclohexene diepoxide (VCD)-induced mouse menopause model, which presents a follicle-depleted and ovary-intact animal that closely approximate the gradual menopause transition in humans. The aim of this study was to compare the impacts of PBDE exposures on the mammary gland at the macroscopic gland structures and the single-cell resolution under three treatment schedules. Materials and Methods We treated nine-week-old female C57BL/6 mice with VCD (160 mg/kg) for 15 days. Then, the animals had high dose PBDE exposure for 1 week during peri- (Perimenopause/High group) or post-menopausal periods (Menopause/High group). The third group was exposed to low dose PBDE (the 1/20th of the high dose) for 20 weeks during the postmenopausal period (Menopause/Low group). In each group, the mice received various combinations of 17B-estradiol and progesterone treatments simultaneously. Our experimental design allowed us to directly compare the effects of PBDE under three potential exposure conditions. Results The mammary glands significantly regressed by the VCD treatment, more evident at the postmenopausal period. All PBDE exposures did not augment or compromise the macroscopic ductal reorganization resulting from the VCD and/or hormonal treatments. Single-cell sequencing revealed that the PBDE exposure in the Menopause/High group caused specific transcriptomic changes in the non-epithelial compartment such as Errfi1 upregulation in fibroblasts and AY036118 downregulation in multiple cell types. The PBDE exposure in the Menopause/Low group resulted in similar transcriptomic changes to a lesser extent. Conclusion PBDEs may affect the postmenopausal gland through impacts on the non-epithelial compartments. Low dose PBDE exposure, which is presumably equivalent to the maximum environmental exposure in humans, can exert the influences. Presentation: No date and time listed

Quantitative MRI can detect early biochemical changes in cartilage; however, the conventional techniques only measure one parameter (e.g., Tsub1/sub, Tsub2/sub, and Tsub1ρ/sub) at a time while also being comparatively slow. We implemented a 3D magnetic resonance fingerprinting (3D-MRF) technique for simultaneous, volumetric mapping of Tsub1/sub, Tsub2/sub, and Tsub1ρ/subin knee articular cartilage in under 9 min. It is evaluated on 11 healthy volunteers (mean age: 53 ± 9 years), five mild knee osteoarthritis (OA) patients (Kellgren-Lawrence (KL) score: 2, mean age: 60 ± 4 years), and the National Institute of Standards and Technology (NIST)/International Society for Magnetic Resonance in Medicine (ISMRM) system phantom. Proton density image, and Tsub1/sub, Tsub2,/subTsub1ρ/subrelaxation times, and Bsub1/subsup+/supwere estimated in the NIST/ISMRM system phantom as well as in the human knee medial and lateral femur, medial and lateral tibia, and patellar cartilage. The repeatability and reproducibility of the proposed technique were assessed in the phantom using analysis of the Bland-Altman plots. The intrasubject repeatability was assessed with the coefficient of variation (CV) and root mean square CV (rmsCV). The Mann-Whitney U test was used to assess the difference between healthy subjects and mild knee OA patients. The Bland-Altman plots in the NIST/ISMRM phantom demonstrated an average difference of 0.001% ± 015%, 1.2% ± 7.1%, and 0.47% ± 3% between two scans from the same 3-T scanner (repeatability), and 0.002% ± 015%, 0.62% ± 10.5%, and 0.97% ± 14% between the scans acquired on two different 3-T scanners (reproducibility) for Tsub1/sub, Tsub2/sub, and Tsub1ρ/sub, respectively. The in vivo knee study showed excellent repeatability with rmsCV less than 1%, 2%, and 1% for Tsub1/sub, Tsub2/sub, and Tsub1ρ/sub, respectively. Tsub1ρ/subrelaxation time in the mild knee OA patients was significantly higher (p lt; 0.05) than in healthy subjects. The proposed 3D-MRF sequence is fast, reproducible, robust to Bsub1/subsup+/supinhomogeneity, and can simultaneously measure the Tsub1/sub, Tsub2/sub, Tsub1ρ/sub, and Bsub1/subsup+/supvolumetric maps of the knee joint in a single scan within a clinically feasible scan time.

Osteoporosis causes bone fragility and elevates fracture risk. Applications of finite element (FE) analysis (FEA) for assessment of trabecular bone (Tb) microstructural strength at whole-body computed tomography (CT) imaging are limited due to challenges with Tb microstructural segmentation. We present a nonlinear FEA method for distal tibia CT scans evading binary segmentation of Tb microstructure, while accounting for bone microstructural distribution. First, the tibial axis in a CT scan was aligned with the FE loading axis. FE cubic mesh elements were modeled using image voxels, and CT intensity values were calibrated to ash density defining mechanical properties at individual elements. For FEA of an upright volume of interest (VOI), the bottom surface was fixed, and a constant displacement was applied at each vertex on the top surface simulating different loading conditions. The method was implemented and optimized using the ANSYS software. CT-derived computational modulus values were repeat scan reproducible (intraclass correlation coefficient [ICC] ≥ 0.97) and highly correlated (

Spondyloarthritis (SpA) is a group of chronic, immune-mediated, inflammatory diseases affecting the bone, synovium, and enthesis. Microbiome, the community of microorganisms that has co-evolved with human hosts, plays a pivotal role in human health and disease. This invisible "essential organ" supplies the host with a myriad of chemicals and molecules. In turn, microbial metabolites can serve as messengers for microbes to communicate with each other and in the cross-talk with host cells. Gut dysbiosis in SpA is associated with altered microbial metabolites, and an accumulated body of research has contributed to the understanding that changes in intestinal microbiota can modulate disease pathogenesis. We review the novel findings from human and animal studies to provide an overview of the contribution of individual microbial metabolites and antigens to SpA.

Regulatory approval of ultrahigh field (UHF) MR imaging scanners for clinical use has opened new opportunities for musculoskeletal imaging applications. UHF MR imaging has unique advantages in terms of signal-to-noise ratio, contrast-to-noise ratio, spectral resolution, and multinuclear applications, thus providing unique information not available at lower field strengths. But UHF also comes with a set of technical challenges that are yet to be resolved and may not be suitable for all imaging applications. This review focuses on the latest research in musculoskeletal MR imaging applications at UHF including morphologic imaging, T2, T2∗, and T1ρ mapping, chemical exchange saturation transfer, sodium imaging, and phosphorus spectroscopy imaging applications.

Twenty men with spinal cord injury (SCI) were randomized into two 16-week intervention groups receiving testosterone treatment (TT) or TT combined with resistance training (TT + RT). TT + RT appears to hold the potential to reverse or slow down bone loss following SCI if provided over a longer period. Persons with SCI experience bone loss below the level of injury. The combined effects of resistance training and TT on bone quality following SCI remain unknown. Men with SCI were randomized into 16-week treatments receiving TT or TT + RT. Magnetic resonance imaging (MRI) of the right lower extremity before participation and post-intervention was used to visualize the proximal, middle, and distal femoral shaft, the quadriceps tendon, and the intermuscular fascia of the quadriceps. For the TT + RT group, MRI microarchitecture techniques were utilized to elucidate trabecular changes around the knee. Individual mixed models were used to estimate effect sizes. Twenty participants completed the pilot trial. A small effect for yellow marrow in the distal femur was indicated as increases following TT and decreases following TT + RT were observed. Another small effect was observed as the TT + RT group displayed greater increases in intermuscular fascia length than the TT arm. Distal femur trabecular changes for the TT + RT group were generally small in effect (decreased trabecular thickness variability, spacing, and spacing variability; increased network area). Medium effects were generally observed in the proximal tibia (increased plate width, trabecular thickness, and network area; decreased trabecular spacing and spacing variability). This pilot suggests longer TT + RT interventions may be a viable rehabilitation technique to combat bone loss following SCI. Registered with clinicaltrials.gov : NCT01652040 (07/27/2012).

Identification of chemicals that affect hormone-regulated systems will help to predict endocrine disruption. In our previous study, a 46 gene biomarker was found to be an accurate predictor of estrogen receptor (ER) α modulation in chemically treated MCF-7 cells. Here, potential ERα modulators were identified using the biomarker by screening a microarray compendium consisting of ∼1600 gene expression comparisons representing exposure to ∼1200 chemicals. A total of ∼170 chemicals were identified as potential ERα modulators. In the Connectivity Map 2.0 collection, 75 and 39 chemicals were predicted to activate or suppress ERα, and they included 12 and six known ERα agonists and antagonists/selective ERα modulators, respectively. Nineteen and eight of the total number were also identified as active in an ERα transactivation assay carried out in an MCF-7-derived cell line used to screen the Tox21 10K chemical library in agonist or antagonist modes, respectively. Chemicals predicted to modulate ERα in MCF-7 cells were examined further using global and targeted gene expression in wild-type and ERα-null cells, transactivation assays, and cell-free ERα coregulator interaction assays. Environmental chemicals classified as weak and very weak agonists were confirmed to activate ERα including apigenin, kaempferol, and oxybenzone. Novel activators included digoxin, nabumetone, ivermectin, and six progestins. Novel suppressors included emetine, mifepristone, niclosamide, and proscillaridin. Our strategy will be useful to identify environmentally relevant ERα modulators in future high-throughput transcriptomic screens.

Acquired resistance to aromatase inhibitors (AIs) is a significant clinical issue in endocrine therapy for estrogen receptor (ER) positive breast cancer which accounts for the majority of breast cancer. Despite estrogen production being suppressed, ERα signaling remains active and plays a key role in most AI-resistant breast tumors. Here, we found that amphiregulin (AREG), an ERα transcriptional target and epidermal growth factor receptor (EGFR) ligand, is crucial for maintaining ERα expression and signaling in acquired AI-resistant breast cancer cells. AREG was deregulated and critical for cell viability in ER+ AI-resistant breast cancer cells, and ectopic expression of AREG in hormone responsive breast cancer cells promoted endocrine resistance. RNA-sequencing and reverse phase protein array analyses revealed that AREG maintains ERα expression and signaling by activation of PI3K/Akt/mTOR signaling and upregulation of Forkhead Box M1 (FoxM1) and Serum- and glucocorticoid-inducible kinase 3 (SGK3) expression. Our study uncovers a previously unappreciated role of AREG in maintaining ERα expression and signaling, and establishes the AREG-ERα crosstalk as a driver of acquired AI resistance in breast cancer.

To evaluate the effect of circular polarization (CP) and elliptical polarization (EP) of the B1 field on metal implant-induced artifacts of titanium (Ti) and cobalt-chromium (CoCr) hip arthroplasty implants at 1.5-T and 3.0-T field strengths. In vitro Ti and CoCr total hip arthroplasty implants were evaluated using high transmit and receive bandwidth turbo spin echo (HBW-TSE) and slice encoding for metal artifact correction (SEMAC) metal artifact reduction techniques. Each technique was implemented at 1.5-T, which only allows for CP of B1 field as the system default, as well as 3.0-T, which permitted CP and EP. Manual segmentation quantified the size of the metal artifacts at the level of the acetabular cup, femoral neck, and femoral shaft. In the acetabular cup and femoral neck, 1.5-T CP achieved smaller artifact sizes than 3.0-T CP (28–29% on HBW-TSE, p = 0.002–0.005; 17–34% on SEMAC, p = 0.019–0.102) and 3.0-T EP (25–28% on HBW-TSE, p = 0.010–0.011; 14–36% on SEMAC, p = 0.058–0.135) techniques. In the femoral stem region, 3.0-T EP achieved more efficient artifact suppression than 3.0-T CP (HBW-TSE 44–45%, p < 0.001–0.022; SEMAC 76–104%, p < 0.001–0.022) and 1.5-T CP (HBW-TSE 76–96%, p < 0.001–0.003; SEMAC 138–173%, p = 0.003–0.005) techniques. Despite slightly superior metal reduction ability of the 1.5-T in the region of the acetabular cup and prosthesis neck, 3.0-T MRI of hip arthroplasty implants using elliptically polarized RF pulses may overall be more effective in reducing metal artifacts than the current standard 1.5-T MRI techniques, which by default implements circularly polarized RF pulses.

Purpose To implement a novel technique for simultaneous, quantitative multiparametric mapping of the knee articular cartilage. Methods A novel MR fingerprinting pulse sequence is proposed and implemented for simultaneous measurements of proton density, T1 , T2, and T1 ρ relaxation times at 3T. The repeatability and reproducibility of the proposed technique were assessed in model phantoms. Institutional review board-approved MR fingerprinting imaging sequence was performed on healthy volunteers and patients with mild knee osteoarthritis. The Wilcoxon test was used to compare healthy controls and patients. The intra- and intersubject repeatability were assessed with coefficient of variation and the RMS coefficient of variation, respectively RESULTS: The Bland-Altman plots demonstrated an average difference of 4.67 ms, -0.09 ms, and 0.05 ms between 2 scans in the same scanner; and 9.68 ms, 0.29 ms, and -0.72 ms between the scans acquired on 2 different scanners for T1 , T2 , and T1 ρ , respectively. The in vivo knee study showed excellent repeatability with RMS coefficient of variation less than 3%, 6%, and 5% for T1 , T2 , and T1 ρ , respectively. The Wilcoxon test showed a significant difference between control and mild osteoarthritis patients for T1 (P = .04), T2 (P = .01), and T1 ρ (P = .02) relaxation time in medial tibial cartilage, as well as for T2 relaxation time (P = .02) in medial femoral cartilage. Conclusion The proposed MRF sequence is fast and can simultaneously measure the T1 , T2 , T1 ρ , and B 1 + maps in a single scan. It is able to discriminate between mild osteoarthritis patients and healthy volunteers.

Background: Estradiol (E2) is known to promote breast cancer. However, several small-scale prospective clinical trials reported the unexpected therapeutic benefit of E2 for aromatase inhibitor (AI)- resistant cases of hormone receptor-positive postmenopausal breast cancer. Considering that the practicality and safety of E2 treatments are still undefined, the objective of this study is to uncover the mechanisms of E2-induced tumor regression, which will lead to a better design of E2 therapies. Methods: While most of our ER+ breast cancer patient-derived xenograft (PDX) models are positively regulated by E2, an estrogen-suppressive model (named GS3) was established from an AI resistant ER+/PR−/HER2− brain metastatic breast cancer. E2 pellets (1mg each) or placebo pellets were implanted in mice carrying GS3 for in vivo drug efficacy examination. Beside tumor growth response, immunohistochemistry (IHC), RNA sequencing, and reverse phase protein array (RPPA) analyses of PDX specimens were conducted to decipher molecular changes after E2 treatments. Importantly, since the cancer tissue has a very heterogeneous structure, the single-cell analysis was further performed to examine gene expression profiles in individual cells. In addition, in vitro cell proliferation analysis was carried out using organoids from GS3. Results: E2 inhibited the growth of GS3 both in vivo and in vitro. ERα and ERβ genes in GS3 are wild-type and not amplified. ERα is involved because E2-mediated inhibition of GS3-organoids can be reversed by the co-treatment of ERα antagonist (MPP), not by ERβ antagonist (PHTPP). IHC showed that PR expression appeared, Ki-67 and CEACAM5 (CEA) expressions decreased, and the number of apoptotic cells significantly increased after E2 treatment. RNA sequencing indicated that estrogen-regulated genes, e.g., PGR, EGR3, PDZK1, and GREB1, were up-regulated, while tumor growth was repressed by E2. Single cell RNAseq analysis demonstrated that cells from E2-treated and Placebo-treated tumors were placed in different clusters based on principle component analysis of Highly Variable Genes (HVGs). Importantly, after one-week, many cells of E2-treated PDXs were arrested within the G1 phase of the cell cycle (G1, 60%; S, 19%; G2M, 21%), whereas, cells of placebo-treated samples advanced to the S and G2M phases (G1, 47%; S, 27%; G2M, 26%). Gene Set Variation Analysis of cells from E2-treated PDXs revealed enrichment of genes associated with reactive oxygen species (ROS) mechanism. E2 increased cells expressing pro-apoptotic genes, such as TP53, BOK,IL24, and PGLYRP2. Gene expressions including mitogen-activated protein kinase (MAPK) signaling pathway, such as GADD45A, MAP3K5 (ASK1), MAPK9 (JNK2), and especially MAPKAPK2 were also increased in E2 treated PDXs. Conclusions: E2/ERα-mediated suppression of GS3 tumor growth was accompanying the inhibition of the cell cycle progression and increased expression of pro-apoptotic genes. It is known that classical MAPK pathway induces cell proliferation, meanwhile, JNK MAPK pathway induces p53 signaling pathway and apoptosis. We hypothesize that E2 induces ROS and promotes apoptosis of GS3 due to JNK MAPK pathway activation. This could be an unexpected outcome of AI resistance. Using this valuable estrogen-down-regulated ER+ breast cancer PDX and informative integrative omics analyses, critical molecular mechanisms on E2-mediated apoptosis are being revealed in our laboratory. The ongoing research using E2-sensitive PDXs will identify key markers to select AI resistant patients who are expected to respond effectively to estrogen-induced apoptosis treatments as well as to evaluate the efficacy of drug combination with estrogen, including CDK 4/6 inhibitors. Citation Format: Hitomi Mori, Kohei Saeki, Gregory Chang, Xiwei Wu, Pei-Yin Hsu, Noriko Kanaya, George Somlo, Shiuan Chen. Estrogen-induced cell cycle arrest and apoptosis in aromatase inhibitor-resistant breast cancer: Insights from single cells analysis of a patient-derived xenograft model [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P1-08-01.

PURPOSE OF REVIEW: Osteoarthritis is a major source of disability, pain and socioeconomic cost worldwide. The epidemiology of the disorder is multifactorial including genetic, biological and biomechanical components, some of them detectable by MRI. This review provides the most recent update on MRI biomarkers which can provide functional information of the joint structures for diagnosis, prognosis and treatment response monitoring in osteoarthritis trials. RECENT FINDINGS: Compositional or functional MRI can provide clinicians with valuable information on glycosaminoglycan content (chemical exchange saturation transfer, sodium MRI, T(1ρ)) and collagen organization (T(2), T(2)*, apparent diffusion coefficient, magnetization transfer) in joint structures. Other parameters may also provide useful information, such as volumetric measurements of joint structures or advanced image data postprocessing and analysis. Automated tools seem to have a great potential to be included in these efforts providing standardization and acceleration of the image data analysis process. SUMMARY: Functional or compositional MRI has great potential to provide noninvasive imaging biomarkers for osteoarthritis. Osteoarthritis as a whole joint condition needs to be diagnosed in early stages to facilitate selection of patients into clinical trials and/or to measure treatment effectiveness. Advanced evaluation including machine learning, neural networks and multidimensional data analysis allow for wall-to-wall understanding of parameter interactions and their role in clinical evaluation of osteoarthritis.

Quantitative MRI can detect early biochemical changes in cartilage, but its bilateral use in clinical routines is challenging. The aim of this prospective study was to demonstrate the feasibility of magnetic resonance fingerprinting for bilateral simultaneous T(1), T(2), and T(1ρ) mapping of the hip joint. The study population consisted of six healthy volunteers with no known trauma or pain in the hip. Monoexponential T(1), T(2), and T(1ρ) relaxation components were assessed in femoral lateral, superolateral, and superomedial, and inferior, as well as acetabular, superolateral, and superomedial subregions in left and right hip cartilage. Aligned ranked nonparametric factorial analysis was used to assess the side’s impact on the subregions. Kruskal–Wallis and Wilcoxon tests were used to compare subregions, and coefficient of variation to assess repeatability. Global averages of T(1) (676.0 ± 45.4 and 687.6 ± 44.5 ms), T(2) (22.5 ± 2.6 and 22.1 ± 2.5 ms), and T(1ρ) (38.2 ± 5.5 and 38.2 ± 5.5 ms) were measured in the left and right hip, and articular cartilage, respectively. The Kruskal–Wallis test showed a significant difference between different subregions’ relaxation times regardless of the hip side (p < 0.001 for T(1), p = 0.012 for T(2), and p < 0.001 for T(lρ)). The Wilcoxon test showed that T(1) of femoral layers was significantly (p < 0.003) higher than that for acetabular cartilage. The experiments showed excellent repeatability with CV(rms) of 1%, 2%, and 4% for T(1), T(2), and T(1ρ,) respectively. It was concluded that bilateral T(1), T(2), and T(1ρ) relaxation times, as well as B(1)(+) maps, can be acquired simultaneously from hip joints using the proposed MRF sequence.

Mammary gland is an essential organ for milk production. It continues to develop after birth under the influence of ovarian hormones, especially estrogen. Among its cellular components, fibroblasts are recognized as an important player for mammary gland organization. Although human mammary gland fibroblasts have been classified into two subtypes based on histological localizations and different marker expressions (i. e., interlobular and intralobular fibroblasts), their detailed characteristics and functions are still limited. Moreover, despite the importance of experimental mouse models for studying mammary gland biology, heterogeneity of mouse mammary gland fibroblasts has not been fully defined. Here, we performed single-cell RNA sequencing (scRNA-seq) to determine cellular populations and their potential contributions to mammary gland organization. Based on the comprehensive gene expression profiles at a single cell level, we identified two major clusters of the mouse mammary gland fibroblasts. One of the major clusters showed the highly specific expression of Dpp4 gene, which is a known marker for human interlobular fibroblasts, and the upregulation of the inflammatory response gene signature. The other major cluster was consisted of three subclusters without Dpp4 expression, which suggested the distinct contributions to adipogenesis and/or ECM modeling in mammary gland stroma. Through the histological validation, we defined these two major subsets as "DPP4+" and "DPP4-" fibroblasts. Since our scRNA-seq was performed on two different ovarian hormone-depleted mouse models followed with hormone treatments, we evaluated the effect of the hormones, especially estrogen. The results demonstrated that the estrogen treatment altered the gene expression profiles of the DPP4+ and a subcluster of the DPP4- fibroblasts in a population-specific manner. Estrogen upregulated interferon-regulated genes and ECM genes in these fibroblast populations, respectively, but not typical estrogen-regulated genes, even in the ERα+ DPP4+ fibroblasts. To define these mammary gland fibroblasts better, we integrated our datasets with a recently established "steady-state mouse fibroblasts atlas" (1) as well as four other scRNA-seq datasets containing normal mouse mammary gland fibroblasts. Using this integrated dataset, we revealed the directional differentiation among the mammary gland fibroblasts, going from the fibroblasts and branching toward the DPP4- fibroblasts with more specialized functions. Moreover, the cell-cell interaction analysis combined with a mammary epithelium dataset from our previous publication (2) indicated possible cell-type-specific communications between mammary gland fibroblasts and epithelial cells. In conclusion, this study provided a comprehensive view of mouse mammary gland fibroblast biology at the single-cell level. Our findings would provide fundamental insights for further investigations on the roles of different fibroblast populations in mammary gland organization and pathological conditions, such as breast cancer. Reference: (1) Buechler et al., Nature. 2021 May;593(7860): 575–579. (2) Saeki et al., Commun Biol. 2021 Jun;4(1): 1–16. Presentation: No date and time listed