Hypothermia protects the integrity of corticospinal tracts and alleviates mitochondria injury after intracerebral hemorrhage in mice.

Disruption of corticospinal tracts (CST) is a leading factor for motor impairments following intracerebral hemorrhage (ICH) in the striatum. Previous studies have shown that therapeutic hypothermia (HT) improves outcomes of ICH patients. However, whether HT has a direct protection effect on the CST integrity and the underlying mechanisms remain largely unknown. In this study, we employed a chemogenetics approach to selectively activate bilateral warm-sensitive neurons in the preoptic areas to induce a hypothermia-like state. We then assessed effects of HT treatment on the integrity of CST and motor functional recovery after ICH. Our results showed that HT treatment significantly alleviated axonal degeneration around the hematoma and the CST axons at remote midbrain region, ultimately promoted skilled motor function recovery. Anterograde and retrograde tracing revealed that HT treatment protected the integrity of the CST over an extended period. Mechanistically, HT treatment prevented mitochondrial swelling in degenerated axons around the hematoma, alleviated mitochondrial impairment by reducing mitochondrial ROS accumulation and improving mitochondrial membrane potential in primarily cultured cortical neurons with oxyhemoglobin treatment. Serving as a proof of principle, our study provided novel insights into the application of HT to improve functional recovery after ICH.

Dual-modal radiomics for predicting cervical lymph node metastasis in papillary thyroid carcinoma.

BACKGROUND: Preoperative prediction of cervical lymph node metastasis (CLNM) in patients with papillary thyroid carcinoma (PTC) is significant for surgical decision-making. OBJECTIVE: This study aims to develop a dual-modal radiomics (DMR) model based on grayscale ultrasound (GSUS) and dual-energy computed tomography (DECT) for non-invasive CLNM in PTC. METHODS: In this study, 348 patients with pathologically confirmed PTC at Jiangsu University Affiliated People's Hospital who completed preoperative ultrasound (US) and DECT examinations were enrolled and randomly assigned to training (n = 261) and test (n = 87) cohorts. The enrolled patients were divided into two groups based on pathology findings namely, CLNM (n = 179) and CLNM-Free (n = 169). Radiomics features were extracted from GSUS images (464 features) and DECT images (960 features), respectively. Pearson correlation coefficient (PCC) and the least absolute shrinkage and selection operator (LASSO) regression with 10-fold cross-validation were then used to select CLNM-related features. Based on the selected features, GSUS, DECT, and GSUS combined DECT radiomics models were constructed by using a Support Vector Machine (SVM) classifier. RESULTS: Three predictive models based on GSUS, DECT, and a combination of GSUS and DECT, yielded performance of areas under the curve (AUC) = 0.700 [95% confidence interval (CI), 0.662-0.706], 0.721 [95% CI, 0.683-0.727], and 0.760 [95% CI, 0.728-0.762] in the training dataset, and AUC = 0.643 [95% CI, 0.582-0.734], 0.680 [95% CI, 0.623-0.772], and 0.744 [95% CI, 0.686-0.784] in the test dataset, respectively. It shows that the predictive model combined GSUS and DECT outperforms both models using GSUS and DECT only. CONCLUSIONS: The newly developed combined radiomics model could more accurately predict CLNM in PTC patients and aid in better surgical planning.

Radiomics features from whole thyroid gland tissue for prediction of cervical lymph node metastasis in the patients with papillary thyroid carcinoma.

OBJECTIVE: We aimed to develop a clinical-radiomics nomogram that could predict the cervical lymph node metastasis (CLNM) of patients with papillary thyroid carcinoma (PTC) using clinical characteristics as well as radiomics features of dual energy computed tomography (DECT). METHOD: Patients from our hospital with suspected PTC who underwent DECT for preoperative assessment between January 2021 and February 2022 were retrospectively recruited. Clinical characteristics were obtained from the medical record system. Clinical characteristics and rad-scores were examined by univariate and multivariate logistic regression. All features were incorporated into the LASSO regression model, with penalty parameter tuning performed using tenfold cross-validation, to screen risk factors for CLNM. An easily accessible radiomics nomogram was constructed. Receiver Operating Characteristic (ROC) curve together with Area Under the Curve (AUC) analysis was conducted to evaluate the discrimination performance of the model. Calibration curves were employed to assess the calibration performance of the clinical-radiomics nomogram, followed by goodness-of-fit testing. Decision curve analysis (DCA) was performed to determine the clinical utility of the established models by estimating net benefits at varying threshold probabilities for training and testing groups. RESULTS: A total of 461 patients were retrospectively recruited. The rates of CLNM were 49.3% (70 /142) in the training cohort and 53.3% (32/60) in the testing cohort. Out of the 960 extracted radiomics features, 192 were significantly different in positive and negative groups (p < 0.05). On the basis of the training cohort, 12 stable features with nonzero coefficients were selected using LASSO regression. LASSO regression identified 7 risk factors for CLNM, including male gender, maximum tumor size > 10 mm, multifocality, CT-reported central CLN status, US-reported central CLN status, rad-score, and TGAb. A nomogram was developed using these factors to predict the risk of CLNM. The AUC values in each cohort were 0.850 and 0.797, respectively. The calibration curve together with the Hosmer-Lemeshow test for the nomogram indicated good agreement between predicted and pathological CLN statuses in the training and testing cohorts. Results of DCA proved that the nomogram offers a superior net benefit for predicting CLNM compared to the "treat all or none" strategy across the majority of risk thresholds. CONCLUSION: A nomogram comprising the clinical characteristics as well as radiomics features of DECT and US was constructed for the prediction of CLNM for patients with PTC, which in determining whether lateral compartment neck dissection is warranted.

Specific Borrmann classification in advanced gastric cancer by an ensemble multilayer perceptron network: a multicenter research.

PURPOSE: Borrmann classification in advanced gastric cancer (AGC) is necessarily associated with personalized surgical strategy and prognosis. But few radiomics research studies have focused on specific Borrmann classification, and there is yet no consensus regarding what machine learning methods should be the most effective. METHODS: A combined size of 889 AGC patients was retrospectively enrolled from two centers. Radiomic features were extracted from tumors manually delineated on preoperative computed tomography images. Two classification experiments (Borrmann I/II/III vs. IV and Borrmann II vs. III) were conducted. In each task, we combined three common feature selection methods and five typical machine learning classifiers to construct 15 basic classification models, and then fed the 15 predictions to a designed multilayer perceptron (MLP) network. RESULTS: In internal and external validation cohorts, the proposed ensemble MLP yielded good performance with area under curves of 0.767 and 0.702 for Borrmann I/II/III vs. IV, as well as 0.768 and 0.731 for Borrmann II vs. III. Considering the imbalanced distribution of four Borrmann types (I, 2.9%; II, 12.8%; III, 69.5%; IV, 14.7%), the ensemble MLP surpassed the overfitting barrier and attained fine specificity (0.667 and 0.750 for Borrmann I/II/III vs. IV; 0.714 and 0.620 for Borrmann II vs. III) and sensitivity (0.795 and 0.610 for Borrmann I/II/III vs. IV; 0.652 and 0.703 for Borrmann II vs. III). Also, survival analysis showed that patients could be significantly risk stratified by MLP predicted types in both experiments (p < 0.0001, log-rank test). CONCLUSIONS: This study proposed an MLP-based ensemble learning architecture, which could identify Borrmann type IV automatically and improve the differentiation of Borrmann type II from III. The study provided a new view for specific Borrmann classification in clinical practice.

Integrating No.3 lymph nodes and primary tumor radiomics to predict lymph node metastasis in T1-2 gastric cancer.

BACKGROUND: This study aimed to develope and validate a radiomics nomogram by integrating the quantitative radiomics characteristics of No.3 lymph nodes (LNs) and primary tumors to better predict preoperative lymph node metastasis (LNM) in T1-2 gastric cancer (GC) patients. METHODS: A total of 159 T1-2 GC patients who had undergone surgery with lymphadenectomy between March 2012 and November 2017 were retrospectively collected and divided into a training cohort (n = 80) and a testing cohort (n = 79). Radiomic features were extracted from both tumor region and No. 3 station LNs based on computed tomography (CT) images per patient. Then, key features were selected using minimum redundancy maximum relevance algorithm and fed into two radiomic signatures, respectively. Meanwhile, the predictive performance of clinical risk factors was studied. Finally, a nomogram was built by merging radiomic signatures and clinical risk factors and evaluated by the area under the receiver operator characteristic curve (AUC) as well as decision curve. RESULTS: Two radiomic signatures, reflecting phenotypes of the tumor and LNs respectively, were significantly associated with LN metastasis. A nomogram incorporating two radiomic signatures and CT-reported LN metastasis status showed good discrimination of LN metastasis in both the training cohort (AUC 0.915; 95% confidence interval [CI] 0.832-0.998) and testing cohort (AUC 0.908; 95% CI 0.814-1.000). The decision curve also indicated its potential clinical usefulness. CONCLUSIONS: The nomogram received favorable predictive accuracy in predicting No.3 LNM in T1-2 GC, and the nomogram showed positive role in predicting LNM in No.4 LNs. The nomogram may be used to predict LNM in T1-2 GC and could assist the choice of therapy.

Intratumoral and peritumoral radiomics analysis for preoperative Lauren classification in gastric cancer.

BACKGROUND: Preoperative prediction of the Lauren classification in gastric cancer (GC) is very important to the choice of therapy, the evaluation of prognosis, and the improvement of quality of life. However, there is not yet radiomics analysis concerning the prediction of Lauren classification straightly. In this study, a radiomic nomogram was developed to preoperatively differentiate Lauren diffuse type from intestinal type in GC. METHODS: A total of 539 GC patients were enrolled in this study and later randomly allocated to two cohorts at a 7:3 ratio for training and validation. Two sets of radiomic features were derived from tumor regions and peritumor regions on venous phase computed tomography (CT) images, respectively. With the least absolute shrinkage and selection operator logistic regression, a combined radiomic signature was constructed. Also, a tumor-based model and a peripheral ring-based model were built for comparison. Afterwards, a radiomic nomogram integrating the combined radiomic signature and clinical characteristics was developed. All the models were evaluated regarding classification ability and clinical usefulness. RESULTS: The combined radiomic signature achieved an area under receiver operating characteristic curve (AUC) of 0.715 (95% confidence interval [CI], 0.663-0.767) in the training cohort and 0.714 (95% CI, 0.636-0.792) in the validation cohort. The radiomic nomogram incorporating the combined radiomic signature, age, CT T stage, and CT N stage outperformed the other models with a training AUC of 0.745 (95% CI, 0.696-0.795) and a validation AUC of 0.758 (95% CI, 0.685-0.831). The significantly improved sensitivity of radiomic nomogram (0.765 and 0.793) indicated better identification of diffuse type GC patients. Further, calibration curves and decision curves demonstrated its great model fitness and clinical usefulness. CONCLUSIONS: The radiomic nomogram involving the combined radiomic signature and clinical characteristics holds potential in differentiating Lauren diffuse type from intestinal type for reasonable clinical treatment strategy.

Development and validation of a CT-based radiomic nomogram for preoperative prediction of early recurrence in advanced gastric cancer.

BACKGROUND: In the clinical management of advanced gastric cancer (AGC), preoperative identification of early recurrence after curative resection is essential. Thus, we aimed to create a CT-based radiomic model to predict early recurrence in AGC patients preoperatively. MATERIALS AND METHODS: We enrolled 669 consecutive patients (302 in the training set, 219 in the internal test set and 148 in the external test set) with clinicopathologically confirmed AGC from two centers. Radiomic features were extracted from preoperative diagnostic CT images. Machine learning methods were applied to shrink feature size and build a predictive radiomic signature. We incorporated the radiomic signature and clinical risk factors into a nomogram using multivariable logistic regression analysis. The area under the curve (AUC) of operating characteristics (ROC), accuracy, and calibration curves were assessed to evaluate the nomogram's performance in discriminating early recurrence. RESULTS: A radiomic signature, including three hand crafted features and six deep learning features, was significantly associated with early recurrence (p-value <0.0001 for all sets). In addition, clinical N stage, carbohydrate antigen 199 levels, carcinoembryonic antigen levels, and Borrmann type were considered useful predictors for early recurrence. The nomogram, combining all these predictors, showed powerful prognostic ability in the training set and two test sets with AUCs of 0.831 (95% CI, 0.786-0.876), 0.826 (0.772-0.880) and 0.806 (0.732-0.881), respectively. The predicted risk yielded good agreement with the observed recurrence probability. CONCLUSIONS: By incorporating a radiomic signature and clinical risk factors, we created a radiomic nomogram to predict early recurrence in patients with AGC, preoperatively, which may serve as a potential tool to guide personalized treatment.

Value of multi-slice spiral computed tomography in the diagnosis of metastatic lymph nodes and N-stage of gastric cancer.

OBJECTIVE: To establish new diagnostic criteria for improvement of the accuracy of multi-slice spiral computed tomography (MSCT) in diagnosing the N-stage and lymph node (LN) metastasis of gastric cancer (GC). METHODS: MSCT was performed with plain and triphasic dynamic contrast enhancement. Different regions of LN metastasis and N-staging were determined according to the herein-proposed combined diagnostic criteria and were then correlated with the pathological analysis. The Kappa consistency test was used to study the accuracy of MSCT. RESULTS: The accuracy of MSCT in diagnosing the N-stage as a whole was 86.3%, and that in diagnosing LN metastasis was 79.1% to 98.9%. The Kappa values for stages N0, N1, and N3 ranged from 0.449 to 0.662, indicating good consistency in diagnosing these three stages between MSCT and the postsurgical pathological results. The Ktotal value was 0.567 between MSCT and the postsurgical pathological results in diagnosing LN metastasis. The risk of LN metastasis increased with the progression of lesion infiltrates. CONCLUSIONS: Application of the combined diagnostic criteria increased the diagnostic performance of MSCT in not only judging the N-stage but also diagnosing LN metastasis. This study will provide valuable reference data for surgical planning for patients with GC in the clinical setting.

Specific Soft-Tissue Invasion and LMP1 Expression Are Potential Indicators of Extranodal NK/T Cell Lymphoma, Nasal Type.

BACKGROUND Extranodal NK/T cell lymphoma, nasal type (ENKTL-NT) is difficult to distinguish from nasal polyps and inverted papilloma, leading to its high misdiagnosis ratio. The aim of this study was to investigate its potential prognostic indicators. MATERIAL AND METHODS Kaplan-Meier method was used to calculate overall survival (OS) rate. Cox proportional hazards regression was used to analyze risk ratios (ORs) with 95% confidence intervals (CIs). RESULTS Nasal ala infiltration and nasal floor thickness >2.0 mm or nasal septum thickness >2.5 mm were potential prognostic factors for OS (p=0.0323 and 0.0072, respectively). Cox proportional-hazards regression indicated that high LMP1 expression and the nasal floor thickness >2.0 mm or nasal septum thickness >2.5 mm were the independent risk factors for poor OS of ENKTL-NT (HR=3.0655, p=0.028; HR=2.3650, p=0.0452, respectively). In the subgroup analysis, the OS rate was lower when the nasal floor thickness >2.0 mm or nasal septum thickness >2.5 mm in the patients who had high expression of LMP1 (p=0.0651), whereas high LMP1 expression increased the risk of worse prognostic outcome in patients with deep infiltration thickness. Thus, high LMP1 expression may contribute to the tissue invasion of ENKTL-NT. CONCLUSIONS Any patient with nasal ala soft-tissue invasion, nasal floor thickness >2.0 mm/nasal septum thickness >2.5 mm on CT imaging or high LMP1 expression should prompt immediate histopathologic diagnosis to rule out ENKTL-NT in clinical practice.

A Functional Iron Oxide Nanoparticles Modified with PLA-PEG-DG as Tumor-Targeted MRI Contrast Agent.

PURPOSE: Tumor targeting could greatly promote the performance of magnetic nanomaterials as MRI (Magnetic Resonance Imaging) agent for tumor diagnosis. Herein, we reported a novel magnetic nanoparticle modified with PLA (poly lactic acid)-PEG (polyethylene glycol)-DG (D-glucosamine) as Tumor-targeted MRI Contrast Agent. METHODS: In this work, we took use of the D-glucose passive targeting on tumor cells, combining it on PLA-PEG through amide reaction, and then wrapped the PLA-PEG-DG up to the Fe3O4@OA NPs. The stability and anti phagocytosis of Fe3O4@OA@PLA-PEG-DG was tested in vitro; the MRI efficiency and toxicity was also detected in vivo. RESULTS: These functional magnetic nanoparticles demonstrated good biocompatibility and stability both in vitro and in vivo. Cell experiments showed that Fe3O4@OA@PLA-PEG-DG nanoparticles exist good anti phagocytosis and high targetability. In vivo MRI images showed that the contrast effect of Fe3O4@OA@PLA-PEG-DG nanoparticles prevailed over the commercial non tumor-targeting magnetic nanomaterials MRI agent at a relatively low dose. CONCLUSIONS: The DG can validly enhance the tumor-targetting effect of Fe3O4@OA@PLA-PEG nanoparticle. Maybe MRI agents with DG can hold promise as tumor-targetting development in the future.

Detection of human breast cancer cells using a 2-deoxy-D-glucose-functionalized superparamagnetic iron oxide nanoparticles.

BACKGROUND: Breast cancer is one of the most common type of female cancer worldwide and represents 14% of cancer-related deaths in women. Early detection is the most important factor for treatment and prognosis of breast cancer. In most countries, the women are currently screened with mammography only. Even though there has been considerable progress in the detection, surgical therapy, hormonal and target therapy of breast cancer, there are about ∼ 3500 000 women who die from breast cancer each year. Therefore, there is an urgent need to explore the new techniques for early detection of breast cancer. Magnetic resonance imaging (MRI) has the potential to improve breast cancer detection at an early stage because of its higher sensitivity. Glucose transporter (Glut) is a cellular transmembrane receptor that plays key roles in cell glucose metabolism and over-expressed in breast cancer cells. 2-deoxy-D-glucose having a similar structure to D-glucose can specifically interact with Glut. METHODS: In the present study, we constructed a 2-deoxy-D-glucose-functionalized superparamagnetic iron oxide (SPIO) nanoparticles that coated with meso-2,3-dimercaptosuccinic acid (γ-Fe2O3@DMSA-DG NPs). The aim of this study is to evaluate the efficacy of new constructed MRI contrast agent (γ-Fe2O3@DMSA-DG NPs) in detecting human breast cancers. RESULTS: Our results showed that breast cancer cells MDA-MD-231, MCF7 and ZR-75-1 had a high uptake rate of γ-Fe2O3@DMSA-DG NPs than human breast fibroblast cell HUM-CELL-0056. There was a significant difference of T2 relaxation times and signal intensity between breast cancer cells and human breast fibroblast cells labeled with γ-Fe2O3@DMSA-DG NPs when MIR. CONCLUSION: Our results indicated that γ-Fe2O3@DMSA-DG NPs may be used as a new MRI contrast agent for detection of breast cancer.

[2-deoxy-D-glucose modified supermagnetic iron oxide nanoparticles enhance the contrasting effect on MRI of human lung adenocarcinoma A549 tumor in nude mice].

OBJECTIVE: To evaluate the role of 2-deoxy-D-glucose (2-DG) modified supermagnetic iron oxide nanoparticles (SPIO) (γ-Fe2O3@DMSA-DG NPs) in tumor detection as a magnetic resonance imaging (MRI) contrast agent. METHODS: γ-Fe2O3@DMSA-DG NPs was prepared. The degree of A549 cells targeted absorption of γ-Fe2O3@DMSA-DG NPs was detected by Prussian blue staining, colorimetric assay, T2W and multi-echo sequence MRI. γ-Fe2O3@DMSA NPs was used as a control agent, and free D-glucose as a competitive inhibitor. Human lung adenocarcinoma A549 xenograft tumor was prepared in nude mice. Sterile aqueous suspension of γ-Fe2O3@DMSA NPs or γ-Fe2O3@DMSA-DG NPs was injected into the tail vein of nude mice. Before and 6, 12, 24, 48 h after injection, MRI imaging of the mice was performed. T2 signal intensity of the tumor, brain, liver and thigh skeletal muscles, and T2 values of the tumors were measured. RESULTS: The average diameter of the particles was about 10 nm, and there were no significant differences between the diameters of γ-Fe2O3@DMSA NPs and γ- Fe2O3@DMSA-DG NPs. The IR spectra showed the C-N retractable vibration peak at γ-Fe2O3@DMSA-DG NPs surface, indicating that 2-DG was conjugated to the γ-Fe2O3@DMSA NPs. The Prussian blue staining, colorimetric assay, MRI T2 signal intensity and T2 values revealed that γ-Fe2O3@DMSA-DG NPs were significantly more absorbed by A549 cells at growth peak than γ-Fe2O3@DMSA NPs, and the absorption of γ-Fe2O3@DMSA-DG NP was inhibited by free D-glucose. The results of in vivo examination showed that before and at 6, 12, 24, 48 h after injection of γ-Fe2O3@DMSA-DG NPs, the mean T2 signal intensities of the tumors were (326.00 ± 16.26)s, (276.40 ± 5.13)s, (268.40 ± 30.58)s, (240.40 ± 25.93)s, (262.20 ± 30.04)s, respectively, and the T2 values of the tumors were (735.80 ± 20.93) ms, (645.80 ± 69.58) ms, (615.00 ± 124.61) ms, (570.60 ± 67.78) ms, and (537.80 ± 105.29) ms, respectively. However, before and at 6, 12, 24, 48 h after injection of γ-Fe2O3@DMSA NPs, the mean T2 signal intensities of the tumors were (335.60 ± 4.93)s, (290.80 ± 5.93)s, (273.40 ± 15.08)s, (327.40 ± 16.65)s, and (313.20 ± 20.45)s, respectively, and T2 values were (686.00 ± 21.44)ms, (617.80 ± 69.93)ms, (645.20 ± 85.89)ms, (669.40 ± 13.72)ms, and (608.80 ± 61.90)ms, respectively. The T2 signal intensity and T2 value of the tumors were not declined generally after injection. The liver T2 signal intensity was decreased after injection of both γ-Fe2O3@DMSA-DG NPs and γ-Fe2O3@DMSA NPs, and T2 signal intensity of the brain and muscle did not show significant changes. CONCLUSIONS: γ-Fe2O3@DMSA-DG NPs has an ability to target glucose receptors overexpressed in tumors, and may serve as a MRI contrast agent for tumor detection.

[Comparison of the targeting properties of 2-deoxy-D-glucose-conjugated nanoparticles to breast cancer MDA-MB-231 cells and breast fibroblasts cells].

OBJECTIVE: To compare the differences in uptake of 2-deoxy-D-glucose (2-DG)-conjugated nanoparticles between breast carcinoma MDA-MB-231 cells with high metabolism and breast fibroblasts with normal metabolism, and investigate the feasibility of using the coated nanoparticles as a MRI-targeted contrast agent for highly metabolic carcinoma cells. METHODS: The γ-Fe2O3@DMSA-DG was prepared. The glucose metabolism level of both cell lines was determined. The targeting efficacy of γ-Fe2O3@DMSA-DG and γ-Fe2O3@DMSA NPs to breast carcinoma MDA-MB-231 cells and breast fibroblasts at 10 min, 30 min, 1 h and 2 h was measured with Prussian blue staining and UV colorimetric assay. MRI was performed to visualize the changes of T2WI signal intensity. RESULTS: Prussian blue staining showed more intracellular blue granules in the MDA-MB-231 cells of γ-Fe2O3@DMSA-DG NPs group than that in the γ-Fe2O3@DMSA NPs group, and the γ-Fe2O3@DMSA-DG uptake was greatly competed by free D-glucose. As revealed by UV colorimetric assay, MDA-MB-231 cells also showed that the cellular iron amount of γ-Fe2O3@DMSA-DG group was significantly higher than that of the γ-Fe2O3@DMSA group and γ-Fe2O3@DMSA-DG + D-glucose group, statistically with a significant difference between them. MRI showed that the signal intensity of γ-Fe2O3@DMSA-DG group was decrease significantly, the T2 signal intensity was decreased by 10.5%, 37.5%, 72.9%, 92.0% for 10 min, 30 min, 1 h and 2 h, respectively. In contrast, the signal intensity did not show obvious decrease in the γ-Fe2O3@DMSA-DG group, the T2 signal intensity was decreased by 8.5%, 11.4%, 32.0%, 76.7% for 10 min, 30 min, 1 h and 2 h, respectively. However, HUM-CELL-0056 cells did not produce apparent difference for positive staining in the γ-Fe2O3@DMSA-DG group, γ-Fe2O3@DMSA group and γ-Fe2O3@DMSA-DG+D-glucose group, and the signal intensity also did not produce apparent difference. CONCLUSIONS: γ-Fe2O3@DMSA-DG has good targeting ability to highly metabolic breast carcinoma (MDA-MB-231) cells. It is feasible to serve as a specific MRI-targeted contrast agent for highly metabolic carcinoma cells, and deserves further studies in vivo.

Necrosis degree displayed in computed tomography images correlated with hypoxia and angiogenesis in breast cancer.

OBJECTIVE: The objective of this study was to investigate the correlation between the degree of necrosis displayed in computed tomography (CT) image and the expression of hypoxic and angiogenesis biomarkers of breast cancer. METHODS: Forty-four breast cancer cases were examined with CT before surgery. Tumor specimen expressions of glucose transporter 1 (Glut1), hypoxia-inducible factor 1α (HIF-1α), carbonic anhydrase IX (CA IX), vascular endothelial growth factor (VEGF), and CD34 (as a marker of vascular endothelial cells) were detected by immunohistochemistry. RESULTS: The expressions of Glut1 and CA IX were localized primarily to the edges of necrotic areas or intraduct surface; there was a strong correlation between HIF-1α-positive expression and CA IX-positive expression (P < 0.001), and higher Glut1 or CA IX expression grade was associated with lower microvessel density (MVD) value. In CT enhanced images, lower relative CT (rCT) values were associated with more significant necrosis in the tumor; rCT value correlated positively with MVD significantly (r = 0.319, P = 0.035), and higher Glut1 or CA IX expression grade correlated with lower rCT values (P = 0.001 and 0.003, respectively). Although high VEGF expression was significantly correlated with high HIF-1α expression (P < 0.001), there were no correlations between VEGF and MVD, and HIF-1α and MVD (P = 0.559 and 0.710, respectively), and the difference of the mean rCT value between high VEGF or HIF-1α expression group and low VEGF or HIF-1α expression group was not significant. CONCLUSIONS: In breast cancer tissues, Glut1 and CA IX are key hypoxia biomarkers. Importantly, detection of necrosis in breast cancer tissue via CT enhanced imaging may prognosticate hypoxia and angiogenesis status and help to determine treatment plan of advanced breast cancer.

Preparation, characterization of 2-deoxy-D-glucose functionalized dimercaptosuccinic acid-coated maghemite nanoparticles for targeting tumor cells.

PURPOSE: To report a modified preparation and to systematically study the structure, magnetic and other properties of γ-Fe(2)O(3)-DMSA-DG NPs (2-deoxy-D-glucose (2-DG) conjugated meso-2,3-dimercaptosuccinic acid coated γ-Fe(2)O(3) nanoparticles) and test its ability to improve Hela tumor cells targeting in vitro compared to the γ-Fe(2)O(3)-DMSA NPs. METHODS: The conjugation of 2-DG on the surface of γ-Fe(2)O(3)-DMSA NPs was performed by esterification reaction and characterized. Acute toxicity was evaluated using MTT assay. Cellular uptake was investigated by Prussian blue staining and UV colorimetric assay. RESULTS: DG was successfully functionalized onto the surface of γ-Fe(2)O(3)-DMSA NPs; binding efficiency was ~60%. The mean diameter of single core of γ-Fe(2)O(3)-DMSA-DG NPs was 10 nm. Particle size and polydispersity index of its aggregates were 156.2 nm and 0.162, respectively. 2-DG-conjugated nanoparticles caused little cytotoxic effects on Hela cells at the concentration range of 0-600 µg/mL. When 2-DG-conjuated and non-conjugated nanoparticles were incubated with Hela cells for 4, 8 and 12 h, the 2-DG-conjugated nanoparticle showed significant amount of uptake in cells compared to their non-targeted counterparts. CONCLUSION: γ-Fe(2)O(3)-DMSA-DG NPs could be developed as a tumor-targeted probe for cervical cancer imaging and therapy.

Mesenchymal stem cell-secreted soluble signaling molecules potentiate tumor growth.

In previous studies, we and others have shown that bone marrow mesenchymal stem cells (MSCs) are recruited to sites of growing tumors and promote tumor growth in mouse xenograft models, suggesting that interactions between MSCs and tumor cells may play an important role in this process. However, the exact mechanism remains unclear. In the present study, we investigated whether the physical presence or the continuous presence of MSCs is required for enhanced tumor growth, and we found that pretreatment of tumor cells SGC-7901 with a single dose of human MSC-conditioned medium (hMSC-CM) in vitro is sufficient to potentiate tumor growth comparable to the effect of MSC co-injection in vivo in mouse xenograft models. We further showed that significant tumor modifying activity is present in post-ultracentrifigation soluble fraction. Biochemical analysis suggests that hMSC-CM induces the expression of VEGF of tumor cells as well as the activation of RhoA-GTPase and ERK1/2. Furthermore, hMSC-CM-enhanced tumor growth is sustainable in serial transplantation, suggesting that MSC-secreted factors have profound effects on "reprogramming" of tumor growth. Our data provide new insights into the way in which MSCs modify tumor growth and offer a new and exciting opportunity to develop effective therapeutics for intercepting tumor progression.

[Uptake of 2-NBDG by human breast cancer cells in vitro].

OBJECTIVE: The purpose of this study was to assess the feasibility of fluorescent 2-deoxyglucose analog, 2-[N-(7-nitrobenz-2-oxa-1, 3-diaxol-4-yl)amino]-2-deoxyglucose (2-NBDG), that could be taken up by breast cancer cells highly expressing glucose transporter 1 (GLUT-1). The purpose of this study was to clarify if a fluorescent 2-deoxyglucose analog, 2-[N-(7-nitrobenz-2-oxa-1, 3-diaxol-4-yl)amino]-2-deoxyglucose (2-NBDG), can be taken up by breast cancer cells highly expressing glucose transporter 1 (GLUT-1), and to assess whether it can be used as a targeting imaging agent. METHODS: The expressions of GLUT-1 mRNA and protein in breast cancer MDA-MB-231 cells were detected by RT-PCR and immunohistochemistry, respectively. The difference of GLUT-1 protein expression between breast cancer MDA-MB-231 cells and MCF-7 cells was compared by Western blot. Secondly, MDA-MB-231 cells which were grown in 6-well plates were incubated with 2-NBDG, and the result of 2-NBDG uptake was analyzed by fluorescence microscopy and flow cytometry. The difference of 2-NBDG absorption in MDA-MB-231 and MCF-7 cells was compared by flow cytometry. RESULTS: The results of RT-PCR and immunohistochemistry confirmed that MDA-MB-231 cells highly expressed GLUT-1. Furthermore, Western blot revealed that GLUT-1 expression of MDA-MB-231 cells (0.946 ± 0.007) was higher than that in the MCF-7 cells (0.833 ± 0.010). Fluorescence microscopic and flow cytometric analysis showed that 2-NBDG was uptaken rapidly by MDA-MB-231 cells. Addition of 50 mmol/L D-glucose to the media with 2-NBDG reduced its uptake by 46.0%. Moreover, flow cytometry indicated that the fluorescence intensity of MDA-MB-231 cells (25.10 ± 0.57) was higher than that of MCF-7 cells (10.12 ± 0.62) when incubated with 2-NBDG for 20 minutes. CONCLUSION: The preliminary data clearly demonstrate that 2-NBDG is taken up and accumulated in breast cancer cells that highly express GLUT-1, and may be used as an optical probe for glucose uptake in hypermetabolic malignant cells.