ABSTRACT
Objective:To explore the effects and the mechanism of metformin combined with celecoxib on the proliferation and apoptosis of hepatoma HepG2 and Huh7 cells.Methods:Hepatoma cells HepG2 and Huh7 were divided into control group, metformin group, celecoxib group and combination medication group, CCK-8 assay was used to detect cell proliferation; Hoechst33258 staining method was used to investigate the cell apoptosis; wound healing test was used to detect cells migration ability; Transwell invasion chamber test was used to detect cell invasion ability; Western blotting was used to detect the expression of AMPK, PI3K, Akt, mTOR.Results:After metformin and celecoxib treatment, HepG2 and Huh7 cells were gradually contracted, disintegrated and more apoptotic cells were noticed, and cell proliferation was significantly inhibited. The wound healing test results showed that the cell migration was significantly decreased ( P<0.05) under metformin and celecoxib treatment. The results of the transwell invasion chamber test showed that the metformin and celecoxib treatment inhibited the invasion of HepG2 and Huh7 cells ( P<0.05). The expression levels of AKT, AMPK, and mTOR were decreased in HepG2 cells in the combinational treatment group, and the expression level of PI3K was decreased and then increased; the expression levels of AKT, AMPK, PI3K, and mTOR in Huh7 cells were decreased. Conclusions:Metformin can cooperate with celecoxib to enhance the inhibitory effect on the proliferation, migration and invasion of HepG2 and Huh7 cells. The mechanism may be related to the inhibition of the expression of mTOR signaling pathway.
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Objective To characterize the biomarkers of urine samples for early diagnosis of colorectal cancer(CRC)using proton nuclear magnetic resonance (1H-NMR)combined with pattern recognition.Methods 400 MHz 1H-NMR was used to test the urine samples obtained from 23 patients with Ⅰ/Ⅱ stage CRC,40 healthy controls (HC)and 18 patients with esophageal cancer (EC). Pattern recognition through orthogonal partial least squares-discriminant analysis (OPLS-DA)was applied on 1H-NMR data to find urine metabolic differences between CRC and HC.Results OPLS-DA could effectively determine HC,patients withⅠ/Ⅱstage CRC and patients with esophageal cancer.Compared with HC,early stage CRC had significant decreases of choline,isocitric acid,lactamine,phenylalan, cysteine,creatinine,aspartic acid,hippurate acid,methylamine,dimethyl sulfone,and increases of acetoacetate,glutamine,glycocyamine,cis-aconitate, trans-aconitate,homocycteine in the urine samples.Conclusion Urine metabonomics based on NMRIndicates that glucose metabolism,amino acid metabolism,choline metabolism,energy metabolism and intestinal microflora are disturbance in colorectal cancer patients,which provide valuable metabolic information on the molecular level for early diagnosis of colorectal cancer.
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Objective To evaluate the diagnostic performance of diffusion kurtosis imaging (DKI) and its combination with DWI and proton MR spectroscopy (1H-MRS) in differentiating malignancy from benign breast lesions. Methods Fifty-three patients with 38 histopathologically confirmed malignant and 15 benign breast lesions were retrospectively studied. The patients were examined by breast MRI at 3.0 T prior to operation, including conventional T1WI, fat-suppression imaging, DWI, DKI and 1H-MRS. The shape and margin of breast lesions, and their corresponding mean values for ADC, mean kurtosis (MK) and mean diffusivity (MD) were determined by two blinded radiologists in consensus. The presence or absence of choline (Cho) peak was identified using LCModel software. Independent-samples t test or χ2 test was performed for the comparison of clinical characteristics, shape and margin of lesions, and imaging parameters between malignancy and benign lesions. ROC analysis was performed to evaluate the diagnostic accuracy of DKI, DWI and 1H-MRS alone or in combination, in comparison with the histopathologic findings. Results The onset age of breast malignancy was higher than that of benign ones, and the difference has statistical significant (P0.05). The mean ADC,MD and MK of benign lesions were(1.464 ± 0.348)× 10-3mm2/s,(1.726 ± 0.268)× 10-3mm2/s and(0.692 ± 0.227), the mean ADC,MD and MK of malignancy were(0.963 ± 0.170)× 10-3mm2/s,(1.158 ± 0.262)× 10-3mm2/s and(1.311 ± 0.218), respectively. Significant differences were obtained between benign and malignant lesions for all parameters (P<0.05).The area under the ROC curve (AUC) of ADC, MD and MK for differentiating malignancy from benign lesions was 0.913, 0.933 and 0.968, respectively. Taken the maximum Youden's index of MK (1.110) as the ROC optimal cut-off point, MK exhibited better diagnostic sensitivity, specificity and accuracy for distinguishing malignancy from benign lesions [89.5%(34/38),93.3%(14/15) and 90.6%(48/53), respectively], compared with MD and ADC. Multiparametric imaging with combination of DKI, DWI and 1H-MRS improves the diagnostic specificity (with the highest as 100.0%) but decreases the sensitivity (with the highest as 81.6% and lowest as 71.1% ), compare with the single parametric imaging. Conclusions MK generated from DKI enables differentiation of breast lesions with a higher diagnostic sensitivity and specificity than DWI and 1H-MRS. DKI combined with DWI and 1H-MRS increase specificity but decrease sensitivity for breast cancer characterization.