RESUMEN
BACKGROUND: We identified the predictive factors and prognostic significance of transarterial chemoembolization (TACE) for achieving pathologic complete response (pCR) before curative surgery for hepatocellular carcinoma (HCC) in hepatitis B-endemic areas. METHODS: Among 753 HCC patients treated with surgery, 124 patients underwent preoperative TACE before liver resection (LR), and 166 before liver transplantation (LT) between 2005 and 2016. Overall survival (OS) and recurrence-free survival (RFS) were analyzed. Pathologic response (PR) was defined as the mean percentage of necrotic area, and pCR was defined as the absence of viable tumor. RESULTS: A total of 34 (27%) and 38 (23%) patients had pCR before LR and LT, respectively. Alpha-fetoprotein (AFP) < 100 ng/mL and single tumor were significant preoperative predictors of pCR. OS and RFS were significantly improved in patients with pCR or a PR ≥ 90%, but not in patients with PR ≥ 50% after LR and LT. On multivariate analyses, PR ≥ 90% remained an independent predictor of better OS and RFS in LR and LT groups. CONCLUSION: Overall, our data clearly demonstrate that pCR predicts favorable prognosis after curative surgery for HCC, and predictors of pCR are AFP <100 ng/mL and single tumor.
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Carcinoma Hepatocelular/mortalidad , Carcinoma Hepatocelular/terapia , Quimioembolización Terapéutica , Neoplasias Hepáticas/mortalidad , Neoplasias Hepáticas/terapia , Biomarcadores/sangre , Carcinoma Hepatocelular/patología , Femenino , Hepatectomía , Humanos , Neoplasias Hepáticas/patología , Trasplante de Hígado , Masculino , Persona de Mediana Edad , Necrosis , Estudios Retrospectivos , alfa-Fetoproteínas/análisisRESUMEN
PURPOSE: Given its heterogeneity and diverse clinical outcomes, precise subclassification of Barcelona Clinic Liver Cancer stage C (BCLC-C) hepatocellular carcinoma (HCC) is required for appropriately determining patient prognosis and selecting treatment. EXPERIMENTAL DESIGN: We recruited 2,626 patients with BCLC-C HCC from multiple centers, comprising training/test (n = 1,693) and validation cohorts (n = 933). The XGBoost model was chosen for maximum performance among the machine learning (ML) models. Patients were categorized into low-, intermediate-, high-, and very high-risk subgroups based on the estimated prognosis, and this subclassification was named the CLAssification via Machine learning of BCLC-C (CLAM-C). RESULTS: The areas under the receiver operating characteristic curve of the CLAM-C for predicting the 6-, 12-, and 24-month survival of patients with BCLC-C were 0.800, 0.831, and 0.715, respectively-significantly higher than those of the conventional models, which were consistent in the validation cohort. The four subgroups had significantly different median overall survivals, and this difference was maintained among various patient subgroups and treatment modalities. Immune-checkpoint inhibitors and transarterial therapies were associated with significantly better survival than tyrosine kinase inhibitors (TKI) in the low- and intermediate-risk subgroups. In cases with first-line systemic therapy, the CLAM-C identified atezolizumab-bevacizumab as the best therapy, particularly in the high-risk group. In cases with later-line systemic therapy, nivolumab had better survival than TKIs in the low-to-intermediate-risk subgroup, whereas TKIs had better survival in the high- to very high-risk subgroup. CONCLUSIONS: ML modeling effectively subclassified patients with BCLC-C HCC, potentially aiding treatment allocation. Our study underscores the potential utilization of ML modeling in terms of prognostication and treatment allocation in patients with BCLC-C HCC.
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Carcinoma Hepatocelular , Neoplasias Hepáticas , Aprendizaje Automático , Humanos , Neoplasias Hepáticas/patología , Neoplasias Hepáticas/mortalidad , Neoplasias Hepáticas/terapia , Neoplasias Hepáticas/tratamiento farmacológico , Neoplasias Hepáticas/diagnóstico , Carcinoma Hepatocelular/patología , Carcinoma Hepatocelular/mortalidad , Carcinoma Hepatocelular/terapia , Carcinoma Hepatocelular/tratamiento farmacológico , Carcinoma Hepatocelular/diagnóstico , Femenino , Masculino , Pronóstico , Persona de Mediana Edad , Anciano , Estadificación de Neoplasias , Algoritmos , Curva ROC , AdultoRESUMEN
Gene-associated with retinoid-interferon-induced mortality 19 (GRIM-19) targets multiple signaling pathways involved in cell death and growth. However, the role of GRIM-19 in the pathogenesis of hepatitis virus infections remains unexplored. Here, we investigated the restrictive effects of GRIM-19 on the replication of hepatitis C virus (HCV). We found that GRIM-19 protein levels were reduced in HCV-infected Huh7 cells and Huh7 cells harboring HCV replicons. Moreover, ectopically expressed GRIM-19 caused a reduction in both intracellular viral RNA levels and secreted viruses in HCVcc-infected cell cultures. The restrictive effect on HCV replication was restored by treatment with siRNA against GRIM-19. Interestingly, GRIM-19 overexpression did not alter the level of phosphorylated STAT3 or its subcellular distribution. Strikingly, forced expression of GRIM-19 attenuated an increase in intracellular lipid droplets after oleic acid (OA) treatment or HCVcc infection. GRIM-19 overexpression abrogated fatty acid-induced upregulation of sterol regulatory element-binding transcription factor-1 (SREBP-1c), resulting in attenuated expression of its target genes such as fatty acid synthase (FAS) and acetyl CoA carboxylase (ACC). Treatment with OA or overexpression of SREBP-1c in GRIM-19-expressing, HCVcc-infected cells restored HCV replication. Our results suggest that GRIM-19 interferes with HCV replication by attenuating intracellular lipid accumulation and therefore is an anti-viral host factor that could be a promising target for HCV treatment.