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Background: Hepatocellular carcinoma (HCC) is one of the most lethal malignancies in the world. Patients with HCC choose postoperative adjuvant transarterial chemoembolization (PA-TACE) after surgical resection to reduce the risk of recurrence. However, many of them have recurrence within a short period. Methods: In this retrospective analysis, a total of 173 patients who underwent PA-TACE between September 2016 and March 2020 were recruited. Radiomic features were derived from the arterial and venous phases of each patient. Early recurrence (ER)-related radiomics features of HCC and the spleen were selected to build two rad-scores using the least absolute shrinkage and selection operator (LASSO) Cox regression analysis. Logistic regression was applied to establish the Radiation (Rad)_score by combining the two regions. We constructed a nomogram containing clinical information and dual-region rad-scores, which was evaluated in terms of discrimination, calibration, and clinical usefulness. Results: All three radiological scores showed good performance for ER prediction. The combined Rad_score performed the best, with an area under the curve (AUC) of 0.853 (95% confidence interval [CI], 0.783-0.908) in the training set and 0.929 (95% CI, 0.789-0.988) in the validation set. Multivariate analysis identified total bilirubin (TBIL) and the combined Rad_score as independent prognostic factors for ER. The nomogram was found to be clinically valuable, as determined by the decision curves (DCA) and clinical impact curves (CIC). Conclusion: A multimodal dual-region radiomics model combining HCC and the spleen is an independent prognostic tool for ER. The combination of dual-region radiomics features and clinicopathological factors has a good clinical application value.
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Background: Hepatocellular carcinoma (HCC) is among malignancies with the highest fatality toll globally and minimal therapeutic options. Necroptosis is a programmed form of necrosis or inflammatory cell death, which can affect prognosis and microenvironmental status of HCC. Therefore, we aimed to explore the prognostic value of necroptosis-related lncRNAs (NRLs) in HCC and the role of the tumor microenvironment (TME) in immunotherapy. Methods: The RNA-sequencing data and clinical information were downloaded from The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC). NRLs were identified by Pearson correlation analysis. The signature was constructed using the LASSO-Cox regression analysis and evaluated using the receiver operating characteristic curve (ROC) and the area under the Kaplan-Meier curve. The nomogram was built based on clinical information and risk score. Gene set enrichment analysis (GSEA), immunoassay, half-maximum inhibitory concentration (IC50) analysis of the risk group, and the HCC subtype identification based on NRLs were also carried out. Finally, we detected the expression of lncRNAs in HCC tissues and cell lines in vitro. Results: A total of 508 NRLs were screened out, and seven NRLs were constructed as a risk stratification system to classify patients into distinct low- and high-risk groups. Patients in the high-risk group had a significantly lower overall survival (OS) than those in the low-risk group. Using multivariate Cox regression analysis, we found that the risk score was an independent predictor of OS. Functional analysis showed that the immune status of different patients was different. The IC50 analysis of chemotherapy demonstrated that patients in the high-risk group were more sensitive to commonly prescribed drugs. qRT-PCR showed that three high-risk lncRNAs were upregulated in drug-resistant cells, and the expression in HCC tissues was higher than that in adjacent tissues. Conclusion: The prediction signature developed in this study can be used to assess the prognosis and microenvironment of HCC patients, and serve as a new benchmark for HCC treatment selection.
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PURPOSE: To explore the predictive value of and the relationship between the gamma-glutamyl transpeptidase (GGT) to lymphocyte ratio (GLR) and computed tomography (CT) features in hepatocellular carcinoma (HCC) patients with postoperative adjuvant transarterial chemoembolization (PA-TACE). METHODS: Between January 2012 and June 2015, 150 HCC patients who underwent adjuvant TACE after hepatectomy in the Affiliated Hospital of Nantong University were selected. Baseline parameters, laboratory values, clinical variables, and CT features (including CT values, irregular rim-like arterial phase enhancement (IRE), and CT enhanced values) were evaluated in all of the patients. The Mann-Whitney U test was performed to assess the GLR values between the patients with microvascular invasion (MVI) and those without MVI. Spearman correlation analysis was performed to evaluate the relationship between IRE and GLR. A nomogram based on the multivariate analysis was constructed. RESULTS: Using multivariate analysis, GLR, MVI, α-fetoprotein levels, and IRE were found to be independent prognostic factors for overall survival (OS). In the MVI group, the GLR of patients was higher than that in the non-MVI group (z=-6.652, p<0.001). We observed a clear correlation between GLR and IRE (r=0.522, p<0.001). The nomogram was constructed and the calibration curve showed excellent predictive performance. CONCLUSIONS: We observed a correlation between GLR and CT features in HCC patients. The nomogram based on clinical data, pathological data, and CT features was suggested to predict the 5-year survival of HCC patients with PA-TACE, which offers an accurate, comprehensive, and reliable evaluation for individualized treatment.