Enhanced glucose metabolism mediated by CD147 contributes to immunosuppression in hepatocellular carcinoma.

From a metabolic perspective, cancer may be considered as a metabolic disease characterized by reprogrammed glycolytic metabolism. The aim of the present study was to investigate CD147-mediated glucose metabolic regulation in hepatocellular carcinoma (HCC) and its contribution to altered immune responses in the tumor microenvironment. Several HCC cell lines and corresponding nude mice xenografts models differing in CD147 expressions were established to directly investigate the role of CD147 in the reprogramming of glucose metabolism, and to determine the underlying molecular mechanisms. Immunohistochemistry (IHC) analyses and flow cytometry were used to identify the relationship between reprogrammed glycolysis and immunosuppression in HCC. Upregulated CD147 expressions were found to be associated with enhanced expressions of GLUT1, MCT1 in HCC tumorous tissues. CD147 promoted the glycolytic metabolism in HCC cell lines in vitro via the PI3K/Akt/mTOR signaling pathway. A positive correlation existed between a profile of immunosuppressive lymphocytes infiltration and CD147 expression in HCC tissues. Accumulation of FOXP3-expressing regulatory T cells was induced under a stimulation with lactate in vitro. In conclusion, CD147 promoted glycolytic metabolism in HCC via the PI3K/Akt/mTOR signaling pathway, and was related to immunosuppression in HCC.

Predictive Power of a Radiomic Signature Based on 18F-FDG PET/CT Images for EGFR Mutational Status in NSCLC.

Radiomics has become an area of interest for tumor characterization in 18F-Fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) imaging. The aim of the present study was to demonstrate how imaging phenotypes was connected to somatic mutations through an integrated analysis of 115 non-small cell lung cancer (NSCLC) patients with somatic mutation testings and engineered computed PET/CT image analytics. A total of 38 radiomic features quantifying tumor morphological, grayscale statistic, and texture features were extracted from the segmented entire-tumor region of interest (ROI) of the primary PET/CT images. The ensembles for boosting machine learning scheme were employed for classification, and the least absolute shrink age and selection operator (LASSO) method was used to select the most predictive radiomic features for the classifiers. A radiomic signature based on both PET and CT radiomic features outperformed individual radiomic features, the PET or CT radiomic signature, and the conventional PET parameters including the maximum standardized uptake value (SUVmax), SUVmean, SUVpeak, metabolic tumor volume (MTV), and total lesion glycolysis (TLG), in discriminating between mutant-type of epidermal growth factor receptor (EGFR) and wild-type of EGFR- cases with an AUC of 0.805, an accuracy of 80.798%, a sensitivity of 0.826 and a specificity of 0.783. Consistently, a combined radiomic signature with clinical factors exhibited a further improved performance in EGFR mutation differentiation in NSCLC. In conclusion, tumor imaging phenotypes that are driven by somatic mutations may be predicted by radiomics based on PET/CT images.

Correlation between EGFR mutation status and F18 -fluorodeoxyglucose positron emission tomography-computed tomography image features in lung adenocarcinoma.

BACKGROUND: The purpose of this study was to investigate an association between EGFR mutation status and 18 F-fluorodeoxyglucose positron emission tomography-computed tomography (18 F-FDG PET-CT) image features in lung adenocarcinoma. METHODS: Retrospective analysis of the data of 139 patients with lung adenocarcinoma confirmed by surgical pathology who underwent preoperative 18 F-FDG PET-CT was conducted. Correlations between EGFR mutation status, clinical characteristics, and PET-CT parameters, including the maximum standardized uptake value (SUVmax), the mean of the SUV (SUVmean), the peak of the SUV (SUVpeak) of the primary tumor, and the ratio of SUVmax between the primary tumor and the mediastinal blood pool (SUVratio), were statistically analyzed. Multivariate logistic regression analysis was performed to identify predictors of EGFR mutation. Receiver operating characteristic curves of statistical quantitative parameters were compared. RESULTS: EGFR mutations were detected in 74 (53.2%) of the 139 lung adenocarcinomas and were more frequent in non-smoking patients. Univariate analysis showed that the SUVmax, SUVmean, SUVpeak, and SUVratio were lower in EGFR-mutated than in wild-type tumors. The receiver operating characteristic curves showed no significant differences between their diagnostic efficiencies. Multivariate logistic regression analysis showed that being a never smoker was an independent predictor of EGFR mutation. CONCLUSION: Quantitative parameters based on 18 F-FDG PET-CT have modest power to predict the presence of EGFR mutation in lung adenocarcinoma; however, when compared to smoking history, they are not good or significant predictive factors.

Value of 18F-FDG PET/CT in diagnosis of single space-occupying lesion of the liver / 中国肿瘤临床

Objective: To evaluate the diagnostic value of PET/CT in single space-occupying lesion of the liver hepatic disease. Meth-ods: Data of 177 patients from Tianjin Medical University Cancer Institute and Hospital between March 2012 and September 2017 with a single hepatic space-occupying lesion who had undergone 18F-FDG PET/CT were collected. CT values and the long and short di-ameters were measured in PACS system. A post-processing workstation was employed, and PETVCAR software was used to automati-cally measure the standardized uptake value (SUV) of the focal and the normal liver tissue. Afterward, T (SUV of the focal)/N (SUV of the normal liver tissue) ratios were calculated. Then, the diagnostic value of various parameters for different pathological types was an-alyzed. The correlation between two continuous variables was calculated using Pearson analysis. Results: The long and short diame-ters of the primary hepatic carcinoma were significantly larger than those of metastatic lesions (P<0.05). The positive rates of hepato-cellular carcinoma (HCC), intrahepatic cholangiocarcinoma (ICC), and metastases were 67.6%, 95.2%, and 98.7%, respectively. All meta-bolic parameters of HCC were significantly lower than those of the other pathological types of liver cancer or metastases (P<0.05). The AUCs for diagnosis of ICC and metastases were higher than 0.5, but there was no statistical difference between the AUCs of different SUVs. Moreover, SUVmax was related to lesion size (r=0.535, P<0.001). Conclusions: 18F-FDG PET/CT has a high positive predictive val-ue and effective diagnostic function for ICC and metastasis, and the diagnostic efficacy for both is higher than that for HCC.