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Background & aims: It remains controversial whether patients with advanced-stage hepatocellular carcinoma could be benefit from transarterial chemoembolization (TACE) treatment. The purpose of the present study is to identify predictors of survival following TACE in patients with advanced HCC. Methods: Overall, 303 patients with Barcelona Clinic Liver Cancer (BCLC) stage C HCC who were first treated with TACE from Sun Yat-sen University Cancer Centre between January 2009 and December 2013 were reviewed and enrolled in this study. We carried out Kaplan-Meier and Cox proportional hazard model analyses of prognostic factors. Results: The median survival of the whole cohort was 8.4 months. Multivariable Cox regression analyses confirmed that four risk factors, high serum levels of gamma-glutamyl transpeptidase (GGT), C-reactive protein (CRP), alkaline phosphatase (ALP) and presence of portal vein tumour thrombosis (PVTT), were independent prognostic factors for overall survival. The expected median survival among patients with 0-1 and 2-4 risk factors were 18.1 (95% CI: 15.5-20.7) and 6.8 (95% CI: 5.8-7.8) months, respectively. Objective tumor response among patients with 0-1 and 2-4 risk factors were 38.9% and 17.3%, respectively. Conclusion: We found four risk factors were associated with dismal overall survival for advanced HCC patients: serum GGT level, serum CRP, serum ALP and presence of PVTT. TACE may be recommended for patients with advanced HCC with 0-1 risk factors due to the favourable prognosis.
Pubmed ID: 30719164
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THIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 5,2022.Tool that predicts interactions between transcription factors and their regulated genes from binding motifs. Understanding vertebrate development requires unraveling the cis-regulatory architecture of gene regulation. PRISM provides accurate genome-wide computational predictions of transcription factor binding sites for the human and mouse genomes, and integrates the predictions with GREAT to provide functional biological context. Together, accurate computational binding site prediction and GREAT produce for each transcription factor: 1. putative binding sites, 2. putative target genes, 3. putative biological roles of the transcription factor, and 4. putative cis-regulatory elements through which the factor regulates each target in each functional role.
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