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Background: There is no effective prognostic signature that could predict the prognosis of nasopharyngeal carcinoma (NPC). Methods: We constructed a prognostic signature based on five microRNAs using random forest and Least Absolute Shrinkage And Selection Operator (LASSO) algorithm on the GSE32960 cohort (N = 213). We verified its prognostic value using three independent external validation cohorts (GSE36682, N = 62; GSE70970, N = 246; and TCGA-HNSC, N = 523). Through principal component analysis, receiver operating characteristic curve analysis, and C-index calculation, we confirmed the predictive accuracy of this prognostic signature. Results: We calculated the risk score based on the LASSO algorithm and divided the patients into high- and low-risk groups according to the calculated optimal cutoff value. The patients in the high-risk group tended to have a worse prognosis outcome and chemotherapy response. The time-dependent receiver operating characteristic curve showed that the 1-year overall survival rate of the five-microRNA signature had an area under the curve of more than 0.83. A functional annotation analysis of the five-microRNA signature showed that the patients in the high-risk group were usually accompanied by activation of DNA repair and MYC-target pathways, while the patients in the low-risk group had higher immune-related pathway signals. Conclusions: We constructed a five-microRNA prognostic signature, which could accurately predict the prognosis of nasopharyngeal carcinoma, and constructed a nomogram that could conveniently predict the overall survival of patients. [ABSTRACT FROM AUTHOR]

BackgroundThere is no effective prognostic signature that could predict the prognosis of nasopharyngeal carcinoma (NPC).MethodsWe constructed a prognostic signature based on five microRNAs using random forest and Least Absolute Shrinkage And Selection Operator (LASSO) algorithm on the GSE32960 cohort (N = 213). We verified its prognostic value using three independent external validation cohorts (GSE36682, N = 62; GSE70970, N = 246; and TCGA-HNSC, N = 523). Through principal component analysis, receiver operating characteristic curve analysis, and C-index calculation, we confirmed the predictive accuracy of this prognostic signature.ResultsWe calculated the risk score based on the LASSO algorithm and divided the patients into high- and low-risk groups according to the calculated optimal cutoff value. The patients in the high-risk group tended to have a worse prognosis outcome and chemotherapy response. The time-dependent receiver operating characteristic curve showed that the 1-year overall survival rate of the five-microRNA signature had an area under the curve of more than 0.83. A functional annotation analysis of the five-microRNA signature showed that the patients in the high-risk group were usually accompanied by activation of DNA repair and MYC-target pathways, while the patients in the low-risk group had higher immune-related pathway signals.ConclusionsWe constructed a five-microRNA prognostic signature, which could accurately predict the prognosis of nasopharyngeal carcinoma, and constructed a nomogram that could conveniently predict the overall survival of patients.

ObjectivesTo investigate the utility of spectral computed tomography (CT) parameters for the prediction of the preoperative Masaoka-Koga stage of thymic epithelial tumors (TETs).Materials and MethodsFifty-four patients with TETs, aged from 37 to 73 years old, an average age of 55.56 ± 9.79 years, were included in the study.According to the Masaoka-Koga staging method, there were 19 cases of stage I, 15 cases of stage II, 8 cases of stage III, and 12 cases of stage IV disease. All patients underwent dual-phase enhanced energy spectral CT scans. Regions of interest (ROIs) were defined in sections of the lesion with homogeneous density, the thoracic aorta at the same level as the lesion, the outer fat layer of the lesion, and the anterior chest wall fat layer. The single-energy CT value at 40-140 keV, iodine concentration, and energy spectrum curve of all lesion and thoracic aorta were obtained. The energy spectrum CT parameters of the lesions, extracapsular fat of the lesions, and anterior chest wall fat in stage I and stage II were obtained. The energy spectrum CT parameters of the lesions, enlarged lymph nodes and intravascular emboli in the 3 groups were obtained. The slope of the energy spectrum curve and the normalized iodine concentration were calculated.ResultsIn stage I lesions, there was a statistically significant difference between the slope of the energy spectrum curve for the lesion and those of the fat outside the lesion and the anterior chest wall in the arteriovenous phase (P0.05). The energy spectrum curve of the tumor parenchyma was consistent with that of the enlarged lymph nodes and intravascular emboli. The two radiologists have strong consistency in evaluating TETs Masaoka-Koga staging, The Kappa coefficient is 0.873,(95%CI:0.768-0.978).ConclusionSpectral CT parameters, especially the energy spectrum curve and slope, are valuable for preoperative TET and can be used in preoperative staging prediction.

Objectives: To investigate the utility of spectral computed tomography (CT) parameters for the prediction of the preoperative Masaoka-Koga stage of thymic epithelial tumors (TETs). Materials and Methods: Fifty-four patients with TETs, aged from 37 to 73 years old, an average age of 55.56 ± 9.79 years, were included in the study.According to the Masaoka-Koga staging method, there were 19 cases of stage I, 15 cases of stage II, 8 cases of stage III, and 12 cases of stage IV disease. All patients underwent dual-phase enhanced energy spectral CT scans. Regions of interest (ROIs) were defined in sections of the lesion with homogeneous density, the thoracic aorta at the same level as the lesion, the outer fat layer of the lesion, and the anterior chest wall fat layer. The single-energy CT value at 40-140 keV, iodine concentration, and energy spectrum curve of all lesion and thoracic aorta were obtained. The energy spectrum CT parameters of the lesions, extracapsular fat of the lesions, and anterior chest wall fat in stage I and stage II were obtained. The energy spectrum CT parameters of the lesions, enlarged lymph nodes and intravascular emboli in the 3 groups were obtained. The slope of the energy spectrum curve and the normalized iodine concentration were calculated. Results: In stage I lesions, there was a statistically significant difference between the slope of the energy spectrum curve for the lesion and those of the fat outside the lesion and the anterior chest wall in the arteriovenous phase (P<0.001, P<0.001). The energy spectrum curve of the tumor parenchyma was the opposite of that of the extracapsular fat. In stage II lesions, there was a statistically significant difference between the slope of the energy spectrum curve for the anterior chest wall and those of the lesion and the fat outside the lesion in the arteriovenous phase(P<0.001, P<0.001). The energy spectrum curve of the tumor parenchyma was consistent with that of the extracapsular fat. Distinction between stage I and II tumors be evaluated by comparing the energy spectrum curves of the mass and the extracapsular fat of the mass. The accuracy rate of is 79.4%. For stages III and IV, there was no significant difference in the slope of the energy spectrum curve of the tumor parenchyma, metastatic lymph node, and intravascular embolism (P>0.05). The energy spectrum curve of the tumor parenchyma was consistent with that of the enlarged lymph nodes and intravascular emboli. The two radiologists have strong consistency in evaluating TETs Masaoka-Koga staging, The Kappa coefficient is 0.873,(95%CI:0.768-0.978). Conclusion: Spectral CT parameters, especially the energy spectrum curve and slope, are valuable for preoperative TET and can be used in preoperative staging prediction. [ABSTRACT FROM AUTHOR]