scholarly journals A prognostic model for predicting recurrence-free survival in hepatocellular carcinoma patients

2020 ◽  
Author(s):  
Wenhua Wang ◽  
Lingchen Wang ◽  
Xinsheng Xie ◽  
Yehong Yan ◽  
Yue Li ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Liver Cancer ◽  
Prognostic Model ◽  
Treatment Plan ◽  
External Validation ◽  
Validation Dataset ◽  
Recurrence Free Survival ◽  
Free Survival ◽  
Liver Cancers ◽  
Robust Likelihood

Abstract Hepatocellular carcinoma (HCC) remains the most frequent liver cancer, accounting for approximately 90% of primary liver cancers worldwide. The recurrence-free survival (RFS) of HCC patients is a critical factor in devising a personal treatment plan. Thus, it is necessary to accurately forecast the prognosis of HCC patients in clinical practice. Using the The Cancer Genome Atlas （TCGA） dataset, we identified genes that are associated with RFS. A robust likelihood-based survival modeling approach was used to select the best genes for the prognostic model. Then, the GSE76427 dataset was used to evaluate the prognostic model’s effectiveness. We identified 1331 differentially expressed genes associated with RFS. Seven of these genes were selected to generate the prognostic model. Validation in both the TCGA cohort and the GEO cohort demonstrated that the 7-gene prognostic model has the capability of predicting the RFS of HCC patients. Meanwhile, the result of multivariate Cox regression showed that the 7-gene prognostic model could work as an independent prognostic factor. In addition, according to the time dependent ROC curve, the 7-gene prognostic model performed better in predicting the RFS of the training set and the external validation dataset than the classical TNM staging and BCLC. What’s more, these seven genes were found to be related to the occurrence and development of liver cancer by exploring other three databases. Our study identified a seven-gene signature for HCC RFS prediction that is a novel and convenient prognostic tool. The seven genes might provide potential target genes for metabolic therapy and the treatment of HCC.

scholarly journals A gene-based risk score model for predicting recurrence-free survival in patients with hepatocellular carcinoma

2020 ◽  
Author(s):  
WENHUA WANG ◽  
LINGCHEN WANG ◽  
XINSHENG XIE ◽  
YEHONG YAN ◽  
YUE LI ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Liver Cancer ◽  
Risk Score ◽  
Prognostic Model ◽  
Validation Dataset ◽  
Recurrence Free Survival ◽  
Free Survival ◽  
Liver Cancers ◽  
Score Model ◽  
Robust Likelihood

Abstract BackgroundHepatocellular carcinoma (HCC) remains the most frequent liver cancer, accounting for approximately 90% of primary liver cancers worldwide. The recurrence-free survival (RFS) of HCC patients is a critical factor in devising a personal treatment plan. Thus, it is necessary to accurately forecast the prognosis of HCC patients in clinical practice.MethodsUsing The Cancer Genome Atlas (TCGA) dataset, we identified genes associated with RFS. A robust likelihood-based survival modeling approach was used to select the best genes for the prognostic model. Then, the GSE76427 dataset was used to evaluate the prognostic model’s effectiveness.ResultsWe identified 1331 differentially expressed genes associated with RFS. Seven of these genes were selected to generate the prognostic model. The validation in both the TCGA cohort and GEO cohort demonstrated that the 7-gene prognostic model can predict the RFS of HCC patients. Meanwhile, the results of the multivariate Cox regression analysis showed that the 7-gene risk score model could function as an independent prognostic factor. In addition, according to the time-dependent ROC curve, the 7-gene risk score model performed better in predicting the RFS of the training set and the external validation dataset than the classical TNM staging and BCLC. Furthermore, these seven genes were found to be related to the occurrence and development of liver cancer by exploring three other databases.ConclusionOur study identified a seven-gene signature for HCC RFS prediction that can be used as a novel and convenient prognostic tool. These seven genes might be potential target genes for metabolic therapy and the treatment of HCC.

scholarly journals A gene-based risk score model for predicting recurrence-free survival in patients with hepatocellular carcinoma

2020 ◽  
Author(s):  
WENHUA WANG ◽  
LINGCHEN WANG ◽  
XINSHENG XIE ◽  
YEHONG YAN ◽  
YUE LI ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Liver Cancer ◽  
Risk Score ◽  
Prognostic Model ◽  
Validation Dataset ◽  
Recurrence Free Survival ◽  
Free Survival ◽  
Liver Cancers ◽  
Score Model ◽  
Robust Likelihood

Abstract BackgroundHepatocellular carcinoma (HCC) remains the most frequent liver cancer, accounting for approximately 90% of primary liver cancers worldwide. The recurrence-free survival (RFS) of HCC patients is a critical factor in devising a personal treatment plan. Thus, it is necessary to accurately forecast the prognosis of HCC patients in clinical practice. MethodsUsing The Cancer Genome Atlas (TCGA) dataset, we identified genes associated with RFS. A robust likelihood-based survival modeling approach was used to select the best genes for the prognostic model. Then, the GSE76427 dataset was used to evaluate the prognostic model’s effectiveness. ResultsWe identified 1331 differentially expressed genes associated with RFS. Seven of these genes were selected to generate the prognostic model. The validation in both the TCGA cohort and GEO cohort demonstrated that the 7-gene prognostic model can predict the RFS of HCC patients. Meanwhile, the results of the multivariate Cox regression analysis showed that the 7-gene risk score model could function as an independent prognostic factor. In addition, according to the time-dependent ROC curve, the 7-gene risk score model performed better in predicting the RFS of the training set and the external validation dataset than the classical TNM staging and BCLC. Furthermore, these seven genes were found to be related to the occurrence and development of liver cancer by exploring three other databases. ConclusionOur study identified a seven-gene signature for HCC RFS prediction that can be used as a novel and convenient prognostic tool. These seven genes might be potential target genes for metabolic therapy and the treatment of HCC.

scholarly journals A gene-based risk score model for predicting recurrence-free survival in patients with hepatocellular carcinoma

2020 ◽  
Author(s):  
Wenhua Wang ◽  
Lingchen Wang ◽  
Xinsheng Xie ◽  
Yehong Yan ◽  
Yue Li ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Liver Cancer ◽  
Risk Score ◽  
Prognostic Model ◽  
Validation Dataset ◽  
Recurrence Free Survival ◽  
Free Survival ◽  
Liver Cancers ◽  
Score Model ◽  
Robust Likelihood

Abstract Background Hepatocellular carcinoma (HCC) remains the most frequent liver cancer, accounting for approximately 90% of primary liver cancers worldwide. The recurrence-free survival (RFS) of HCC patients is a critical factor in devising a personal treatment plan. Thus, it is necessary to accurately forecast the prognosis of HCC patients in clinical practice.Methods Using The Cancer Genome Atlas (TCGA) dataset, we identified genes associated with RFS. A robust likelihood-based survival modeling approach was used to select the best genes for the prognostic model. Then, the GSE76427 dataset was used to evaluate the prognostic model’s effectiveness. Results We identified 1331 differentially expressed genes associated with RFS. Seven of these genes were selected to generate the prognostic model. The validation in both the TCGA cohort and GEO cohort demonstrated that the 7-gene prognostic model can predict the RFS of HCC patients. Meanwhile, the results of the multivariate Cox regression analysis showed that the 7-gene risk score model could function as an independent prognostic factor. In addition, according to the time-dependent ROC curve, the 7-gene risk score model performed better in predicting the RFS of the training set and the external validation dataset than the classical TNM staging and BCLC. Furthermore, these seven genes were found to be related to the occurrence and development of liver cancer by exploring three other databases. Conclusion Our study identified a seven-gene signature for HCC RFS prediction that can be used as a novel and convenient prognostic tool. These seven genes might be potential target genes for metabolic therapy and the treatment of HCC.

scholarly journals A gene-based risk score model for predicting recurrence-free survival in patients with hepatocellular carcinoma

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Wenhua Wang ◽  
Lingchen Wang ◽  
Xinsheng Xie ◽  
Yehong Yan ◽  
Yue Li ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Liver Cancer ◽  
Risk Score ◽  
Prognostic Model ◽  
Validation Dataset ◽  
Recurrence Free Survival ◽  
Free Survival ◽  
Liver Cancers ◽  
Score Model ◽  
Robust Likelihood

Abstract Background Hepatocellular carcinoma (HCC) remains the most frequent liver cancer, accounting for approximately 90% of primary liver cancers worldwide. The recurrence-free survival (RFS) of HCC patients is a critical factor in devising a personal treatment plan. Thus, it is necessary to accurately forecast the prognosis of HCC patients in clinical practice. Methods Using The Cancer Genome Atlas (TCGA) dataset, we identified genes associated with RFS. A robust likelihood-based survival modeling approach was used to select the best genes for the prognostic model. Then, the GSE76427 dataset was used to evaluate the prognostic model’s effectiveness. Results We identified 1331 differentially expressed genes associated with RFS. Seven of these genes were selected to generate the prognostic model. The validation in both the TCGA cohort and GEO cohort demonstrated that the 7-gene prognostic model can predict the RFS of HCC patients. Meanwhile, the results of the multivariate Cox regression analysis showed that the 7-gene risk score model could function as an independent prognostic factor. In addition, according to the time-dependent ROC curve, the 7-gene risk score model performed better in predicting the RFS of the training set and the external validation dataset than the classical TNM staging and BCLC. Furthermore, these seven genes were found to be related to the occurrence and development of liver cancer by exploring three other databases. Conclusion Our study identified a seven-gene signature for HCC RFS prediction that can be used as a novel and convenient prognostic tool. These seven genes might be potential target genes for metabolic therapy and the treatment of HCC.

scholarly journals Downregulation of CYP2A6 and CYP2C8 in Tumor Tissues Is Linked to Worse Overall Survival and Recurrence-Free Survival from Hepatocellular Carcinoma

2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Xiaojing Ren ◽  
Yuanyuan Ji ◽  
Xuhua Jiang ◽  
Xun Qi
Keyword(s):  
Hepatocellular Carcinoma ◽  
Overall Survival ◽  
Tumor Staging ◽  
Gene Expression Omnibus ◽  
Intrahepatic Metastasis ◽  
Clinicopathological Features ◽  
Validation Dataset ◽  
Recurrence Free Survival ◽  
Free Survival ◽  
Tumor Tissues

Objective. This study aimed to evaluate the links between CYP450 family genes in tumor tissues and hepatocellular carcinoma (HCC) outcomes.Methods. Gene Expression Omnibus (GEO) databases GSE14520 and GSE36376 were used to identify differential expressed CYP450 genes between tumor and nontumor tissues and related to HCC clinicopathological features and survivals.Results. Seven CYP450 genes including CYP1A2, CYP2A6, CYP2C8, CYP2C9, CYP2E1, CYP3A4, and CYP4A11 were downregulated in tumor tissues, which were validated in both GSE14520 and GSE36376. HCC patients with CYP2A6 and CYP2C8 low levels in tumor tissues suffered from poorer overall survival (OS) compared to those with high CYP2A6 and CYP2C8 in GSE14520 profile (log ranksP= 0.01 andP= 0.006, respectively). In addition, HCC patients with lower CYP2A6 and CYP2C8 in tumors had worse recurrence-free survival (RFS) than those with higher CYP2A6 and CYP2C8 (log ranksP= 0.02 andP= 0.012, respectively). In GSE36376 validation dataset, HCC patients with lower CYP2A6 and CYP2C8 had worse OS and RFS than those with higher CYP2A6 and CYP2C8 (allP< 0.05), in line with results in GSE14520 dataset. Additionally, lower CYP2A6 and CYP2C8 are associated with advanced clinicopathological features including tumor staging, vascular invasion, intrahepatic metastasis, and high alpha fetoprotein (allP< 0.05).Conclusion. Downregulation of CYP2A6 and CYP2C8 in tumor tissues links to poorer OS and RFS in HCC patients.

scholarly journals Clinical features and outcomes of combined hepatocellular carcinoma and cholangiocarcinoma versus hepatocellular carcinoma versus cholangiocarcinoma after surgical resection: a propensity score matching analysis

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Chih-Wen Lin ◽  
Tsung-Chin Wu ◽  
Hung-Yu Lin ◽  
Chao-Ming Hung ◽  
Pei-Min Hsieh ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Liver Cancer ◽  
Propensity Score ◽  
Propensity Score Matching ◽  
Surgical Resection ◽  
Disease Free Survival ◽  
Clinicopathological Features ◽  
Free Survival ◽  
Before And After ◽  
Disease Free

Abstract Background Combined hepatocellular carcinoma and cholangiocarcinoma (cHCC-CC) is an infrequent type of primary liver cancer that comprises hepatocellular carcinoma (HCC) and cholangiocarcinoma (CC). This study investigated the clinicopathological features and prognosis among cHCC-CC, HCC, and CC groups. Methods We prospectively collected the data of 608 patients who underwent surgical resection for liver cancer between 2011 and 2018 at E-Da Hospital, I-Shou University, Kaohsiung, Taiwan. Overall, 505 patients with cHCC-CC, HCC, and CC were included, and their clinicopathological features, overall survival (OS), and recurrence were recorded. OS and recurrence rates were analyzed using the Kaplan–Meier analysis. Results In the entire cohort, the median age was 61 years and 80% were men. Thirty-five (7.0%) had cHCC-CC, 419 (82.9%) had HCC, and 51 (10.1%) had CC. The clinicopathological features of the cHCC-CC group were more identical to those of the HCC group than the CC group. OS was significantly lower in the cHCC-CC group than in the HCC group but was not significantly higher in the cHCC-CC group than in the CC group. The median OS of cHCC-CC, HCC, and CC groups was 50.1 months [95% confidence interval (CI): 38.7–61.2], 62.3 months (CI: 42.1–72.9), and 36.2 months (CI: 15.4–56.5), respectively. Cumulative OS rates at 1, 3, and 5 years in cHCC-CC, HCC, and CC groups were 88.5%, 62.2%, and 44.0%; 91.2%, 76.1%, and 68.0%; and 72.0%, 48.1%, and 34.5%, respectively. After propensity score matching (PSM), OS in the cHCC-CC group was not significantly different from that in the HCC or CC group. However, OS was significantly higher in the HCC group than in the CC group before and after PSM. Furthermore, the disease-free survival was not significantly different among cHCC-CC, HCC, and CC groups before and after PSM. Conclusion The clinicopathological features of the cHCC-CC group were more identical to those of the HCC group than the CC group. The OS rate was significantly lower in the cHCC-CC group than the HCC group. However, after PSM, OS and disease-free survival in the cHCC-CC group were not significantly different from those in the HCC or CC group.

scholarly journals Inflammatory indexes in preoperative blood routine to predict early recurrence of hepatocellular carcinoma after curative hepatectomy

BMC Surgery ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
YiFeng Wu ◽  
ChaoYong Tu ◽  
ChuXiao Shao
Keyword(s):  
Risk Factors ◽  
Hepatocellular Carcinoma ◽  
Tumour Size ◽  
Area Under The Curve ◽  
Early Recurrence ◽  
Recurrence Free Survival ◽  
Free Survival ◽  
Lymphocyte Ratio ◽  
Inflammatory Index ◽  
Curative Hepatectomy

Abstract Background The inflammation indexes in blood routine play an essential role in evaluating the prognosis of patients with hepatocellular carcinoma, but the effect on early recurrence has not been clarified. The study aimed to investigate the risk factors of early recurrence (within 2 years) and recurrence-free survival after curative hepatectomy and explore the role of inflammatory indexes in predicting early recurrence. Methods The baseline data of 161 patients with hepatocellular carcinoma were analyzed retrospectively. The optimal cut-off value of the inflammatory index was determined according to the Youden index. Its predictive performance was compared by the area under the receiver operating characteristic curve. Logistic and Cox regression analyses were used to determine the risk factors of early recurrence and recurrence-free survival. Results The area under the curve of monocyte to lymphocyte ratio (MLR) for predicting early recurrence was 0.700, which was better than systemic inflammatory response index (SIRI), neutrophil to lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR) and systemic immune-inflammatory index (SII). MLR, tumour size, tumour differentiation and BCLC stage are all risk factors for early recurrence and recurrence-free survival of HCC. Combining the above four risk factors to construct a joint index, the area under the curve for predicting early recurrence was 0.829, which was better than single MLR, tumour size, tumour differentiation and BCLC stage. Furthermore, with the increase of risk factors, the recurrence-free survival of patients is worse. Conclusion The combination of MLR and clinical risk factors is helpful for clinicians to identify high-risk patients with early recurrence and carry out active postoperative adjuvant therapy to improve the prognosis of patients.

Radiofrequency Ablation With or Without Transcatheter Arterial Chemoembolization in the Treatment of Hepatocellular Carcinoma: A Prospective Randomized Trial

2013 ◽  
Vol 31 (4) ◽  
pp. 426-432 ◽  
Author(s):  
Zhen-Wei Peng ◽  
Yao-Jun Zhang ◽  
Min-Shan Chen ◽  
Li Xu ◽  
Hui-Hong Liang ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Overall Survival ◽  
Prognostic Factors ◽  
Transcatheter Arterial Chemoembolization ◽  
Recurrence Free Survival ◽  
Treatment Allocation ◽  
Free Survival ◽  
End Point ◽  
Tumor Number ◽  
Arterial Chemoembolization

Purpose To compare radiofrequency ablation (RFA) with or without transcatheter arterial chemoembolization (TACE) in the treatment of hepatocellular carcinoma (HCC). Patients and Methods A randomized controlled trial was conducted on 189 patients with HCC less than 7 cm at a single tertiary referral center between October 2006 and June 2009. Patients were randomly asssigned to receive TACE combined with RFA (TACE-RFA; n = 94) or RFA alone (n = 95). The primary end point was overall survival. The secondary end point was recurrence-free survival, and the tertiary end point was adverse effects. Results At a follow-up of 7 to 62 months, 34 patients in the TACE-RFA group and 48 patients in the RFA group had died. Thirty-three patients and 52 patients had developed recurrence in the TACE-RFA group and RFA group, respectively. The 1-, 3-, and 4-year overall survivals for the TACE-RFA group and the RFA group were 92.6%, 66.6%, and 61.8% and 85.3%, 59%, and 45.0%, respectively. The corresponding recurrence-free survivals were 79.4%, 60.6%, and 54.8% and 66.7%, 44.2%, and 38.9%, respectively. Patients in the TACE-RFA group had better overall survival and recurrence-free survival than patients in the RFA group (hazard ratio, 0.525; 95% CI, 0.335 to 0.822; P = .002; hazard ratio, 0.575; 95% CI, 0.374 to 0.897; P = .009, respectively). There were no treatment-related deaths. On logistic regression analyses, treatment allocation, tumor size, and tumor number were significant prognostic factors for overall survival, whereas treatment allocation and tumor number were significant prognostic factors for recurrence-free survival. Conclusion TACE-RFA was superior to RFA alone in improving survival for patients with HCC less than 7 cm.

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