Summary In a prospective trial of 75 Chinese patients with histologically proven inoperable hepatocellular carcinoma (HCC), 25 patients were randomised to receive doxorubicin 60-75 mg m2 intravenously once every 3 weeks, 25 to receive recombinant M2 interferon (rIFN) (Roferon) 9-18 x 106 IU m-2 intramuscularly (i.m.) daily and 25 to receive rIFN 25-50 x 106 IU m-2 i.m. three times weekly. Patients were switched to the other drug if: (a) there was progressive disease after 12 weeks, (b) unacceptable toxicity developed and (c) they had received a total of 500 mg m2 of doxorubicin. Six patients had switching over of therapy, three on doxorubicin and three on rIFN. In the remaining 69 patients on single drug therapy, the median survival rate of patients on doxorubicin and rIFN was 4.8 and 8.3 weeks respectively (P = ns.). rIFN induced tumour regression of 25-50% in 12% of patients and of over 50% in 10% of patients. When compared with doxorubicin, rIFN was associated with more tumour regression (P = 0.00199) and less progressive tumours (P= 0.00017). It caused less prolonged and less severe marrow suppression (P= 0.01217), and had significantly less fatal complications than doxorubicin (P = 0.01383). Doxorubicin caused fatal complications due to cardiotoxicity and neutropenia in 25% of patients. rIFN was associated with fatal complications due to dementia and renal failure in 3.8% of patients. In the treatment of inoperable HCC, rIFN is superior to doxorubicin in causing more tumour regression, less serious marrow suppression and less fatal complications.
Colorectal cancer (CRC) remains a major health problem worldwide and the detailed mechanisms of CRC still need further understanding. Circular RNAs (circRNAs), a special class of endogenous RNAs, have emerged recently as a new potential player in governing fundamental biological process and cancer progression. In this study, we chose circRNA0003906 as a targeted circRNA to evaluate its expression pattern and clinical value in CRC patients. circRNA0003906 expression level in 6 CRC cell lines and 122 paired CRC tissues was measured by quantitative real-time polymerase chain reaction. Then, the potential correlation between circRNA0003906 expression level and clinicopathological factors of CRC patients was analyzed. Additionally, a receiver operating characteristic curve was built to evaluate the diagnostic value of circRNA0003906. Our results showed that circRNA0003906 expression level was dramatically downregulated in both CRC tissues and cell lines. Moreover, the downregulation of circRNA0003906 level significantly correlated with lymphatic metastasis and poor differentiation. In addition, the area under the receiver operating characteristic curve of circRNA0003906 for CRC was 0.818 (P<0.001). Taking consideration of all of these results, circRNA0003906 may be potentially involved in the colorectal cancerogenesis and serve as a potential biomarker for the diagnosis and treatment of CRC.
AimTo evaluate the feasibility of computed tomography (CT) - derived measurements of body composition parameters to predict the risk factor of non-objective response (non-OR) in patients with hepatocellular carcinoma (HCC) undergoing anti-PD-1 immunotherapy and hepatic artery infusion chemotherapy (immune-HAIC).MethodsPatients with histologically confirmed HCC and treated with the immune-HAIC were retrospectively recruited between June 30, 2019, and July 31, 2021. CT-based estimations of body composition parameters were acquired from the baseline unenhanced abdominal CT images at the level of the third lumbar vertebra (L3) and were applied to develop models predicting the probability of OR. A myosteatosis nomogram was built using the multivariate logistic regression incorporating both myosteatosis measurements and clinical variables. Receiver operating characteristic (ROC) curves assessed the performance of prediction models, including the area under the curve (AUC). The nomogram’s performance was assessed by the calibration, discrimination, and decision curve analyses. Associations among predictors and gene mutations were also examined by correlation matrix analysis.ResultsFifty-two patients were recruited to this study cohort, with 30 patients having a OR status after immune-HAIC treatment. Estimations of myosteatosis parameters, like SM-RA (skeletal muscle radiation attenuation), were significantly associated with the probability of predicting OR (P=0.007). The SM-RA combined nomogram model, including serum red blood cell, hemoglobin, creatinine, and the mean CT value of visceral fat (VFmean) improved the prediction probability for OR disease with an AUC of 0.713 (95% CI, 0.75 to 0.95) than the clinical model nomogram with AUC of 0.62 using a 5-fold cross-validation methodology. Favorable clinical potentials were observed in the decision curve analysis.ConclusionsThe CT-based estimations of myosteatosis could be used as an indicator to predict a higher risk of transition to the Non-OR disease state in HCC patients treated with immune-HAIC therapy. This study demonstrated the therapeutic relevance of skeletal muscle composition assessments in the overall prediction of treatment response and prognosis in HCC patients.
ObjectivesStandard magnetic resonance imaging (MRI) techniques are different to distinguish minimal fat angiomyolipoma (mf-AML) with minimal fat from renal cell carcinoma (RCC). Here we aimed to evaluate the diagnostic performance of MRI-based radiomics in the differentiation of fat-poor AMLs from other renal neoplasms.MethodsA total of 69 patients with solid renal tumors without macroscopic fat and with a pathologic diagnosis of RCC (n=50) or mf-AML (n=19) who underwent conventional MRI and intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) were included. Clinical data including age, sex, tumor location, urine creatinine, and urea nitrogen were collected from medical records. The apparent diffusion coefficient (ADC), pure diffusion coefficient (D), pseudodiffusion coefficient (D*), and perfusion fraction (f) were measured from renal tumors. We used the ITK-SNAP software to manually delineate the regions of interest on T2-weighted imaging (T2WI) and IVIM-DWI from the largest cross-sectional area of the tumor. We extracted 396 radiomics features by the Analysis Kit software for each MR sequence. The hand-crafted features were selected by using the Pearson correlation analysis and least absolute shrinkage and selection operator (LASSO). Diagnostic models were built by logistic regression analysis. Receiver operating characteristic curve analysis was performed using five-fold cross-validation and the mean area under the curve (AUC) values were calculated and compared between the models to obtain the optimal model for the differentiation of mf-AML and RCC. Decision curve analysis (DCA) was used to evaluate the clinical utility of the models.ResultsClinical model based on urine creatinine achieved an AUC of 0.802 (95%CI: 0.761-0.843). IVIM-based model based on f value achieved an AUC of 0.692 (95%CI: 0.627-0.757). T2WI-radiomics model achieved an AUC of 0.883 (95%CI: 0.852-0.914). IVIM-radiomics model achieved an AUC of 0.874 (95%CI: 0.841-0.907). Combined radiomics model achieved an AUC of 0.919 (95%CI: 0.894-0.944). Clinical-radiomics model yielded the best performance, with an AUC of 0.931 (95%CI: 0.907-0.955). The calibration curve and DCA confirmed that the clinical-radiomics model had a good consistency and clinical usefulness.ConclusionThe clinical-radiomics model may be served as a noninvasive diagnostic tool to differentiate mf-AML with RCC, which might facilitate the clinical decision-making process.
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