scholarly journals Prognostic value of a novel risk classification of microvascular invasion in patients with hepatocellular carcinoma after resection

Oncotarget ◽  
2016 ◽  
Vol 8 (3) ◽  
pp. 5474-5486 ◽  
Author(s):  
Hui Zhao ◽  
Chuang Chen ◽  
Xu Fu ◽  
Xiaopeng Yan ◽  
Wenjun Jia ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Prognostic Value ◽  
Risk Classification ◽  
Microvascular Invasion

Prognostic Value and Prediction of Extratumoral Microvascular Invasion for Hepatocellular Carcinoma

2019 ◽  
Vol 26 (8) ◽  
pp. 2568-2576 ◽  
Author(s):  
Hidetoshi Nitta ◽  
Marc-Antoine Allard ◽  
Mylène Sebagh ◽  
Oriana Ciacio ◽  
Gabriella Pittau ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Prognostic Value ◽  
Microvascular Invasion

scholarly journals A predictive and prognostic model for hepatocellular carcinoma with microvascular invasion based TCGA database genomics

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Jin Wang ◽  
Zhi-Wen Ding ◽  
Kuang Chen ◽  
Yan-Zhe Liu ◽  
Nan Li ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Survival Analysis ◽  
Prediction Model ◽  
Prognostic Value ◽  
Tissue Microarrays ◽  
Microvascular Invasion ◽  
Classification Model ◽  
Term Survival ◽  
Significant Difference ◽  
Key Genes

Abstract Background Microvascular invasion (MVI) adversely affects postoperative long-term survival outcomes in patients with hepatocellular carcinoma (HCC). There is no study addressing genetic changes in HCC patients with MVI. We first screened differentially expressed genes (DEGs) in patients with and without MVI based on TCGA data, established a prediction model and explored the prognostic value of DEGs for HCC patients with MVI. Methods In this paper, gene expression and clinical data of liver cancer patients were downloaded from the TCGA database. The DEG analysis was conducted using DESeq2. Using the least absolute shrinkage and selection operator, MVI-status-related genes were identified. A Kaplan-Meier survival analysis was performed using these genes. Finally, we validated two genes, HOXD9 and HOXD10, using two sets of HCC tissue microarrays from 260 patients. Results Twenty-three MVI-status-related key genes were identified. Based on the key genes, we built a classification model using random forest and time-dependent receiver operating characteristic (ROC), which reached 0.814. Then, we performed a survival analysis and found ten genes had a significant difference in survival time. Simultaneously, using two sets of 260 patients’ HCC tissue microarrays, we validated two key genes, HOXD9 and HOXD10. Our study indicated that HOXD9 and HOXD10 were overexpressed in HCC patients with MVI compared with patients without MVI, and patients with MVI with HOXD9 and 10 overexpression had a poorer prognosis than patients with MVI with low expression of HOXD9 and 10. Conclusion We established an accurate TCGA database-based genomics prediction model for preoperative MVI risk and studied the prognostic value of DEGs for HCC patients with MVI. These DEGs that are related to MVI warrant further study regarding the occurrence and development of MVI.

scholarly journals Identification and validation of a five-gene prognostic signature for hepatocellular carcinoma

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Huibin Yang ◽  
Junyu Huo ◽  
Xin Li
Keyword(s):  
Hepatocellular Carcinoma ◽  
Overall Survival ◽  
Cox Regression ◽  
Human Cancer ◽  
External Validation ◽  
Enrichment Analysis ◽  
Risk Classification ◽  
Gene Set Enrichment Analysis ◽  
Prognostic Signature

Abstract Background ARID1A is a commonly mutated tumor suppressor gene found in all human cancer types, but its clinical significance, oncogenic functions, and relevant mechanisms in hepatocellular carcinoma (HCC) are not well understood. Objective We aimed to improving the prognosis risk classification of HCC from the perspective of ARID1A mutations. Materials and methods We examined the interaction between ARID1A mutations and the overall survival via Kaplan-Meier survival analysis. We used gene set enrichment analysis (GSEA) to elucidate the influence of ARID1A mutations on signaling pathways. A prognostic model was constructed using LASSO and multivariate Cox regression analyses. A receiver operating characteristic (ROC) curve was used to estimate the performance and accuracy of the model. Results HCC patients with ARID1A mutations presented poor prognosis. By GSEA, we showed that genes upregulated by reactive oxygen species (ROS) and regulated by MYC were positively correlated with ARID1A mutations. A prognostic signature consisting of 5 genes (SRXN1, LDHA, TFDP1, PPM1G, and EIF2S1) was constructed in our research. The signature showed good performance in predicting overall survival (OS) for HCC patients by internal and external validation. Conclusion Our research proposed a novel and robust approach for the prognostic risk classification of HCC patients, and this approach may provide new insights to improve the treatment strategy of HCC.

scholarly journals Prognostic Value of Microvascular Invasion in Eight Existing Staging Systems for Hepatocellular Carcinoma: A Bi-Centeric Retrospective Cohort Study

2021 ◽  
Vol 11 ◽  
Author(s):  
Yan-Jun Xiang ◽  
Kang Wang ◽  
Yi-Tao Zheng ◽  
Hong-Ming Yu ◽  
Yu-Qiang Cheng ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Liver Cancer ◽  
Prognostic Value ◽  
Staging System ◽  
Microvascular Invasion ◽  
Survival Outcomes ◽  
Entire Cohort ◽  
Significant Survival ◽  
Staging Systems ◽  
Survival Differences

BackgroundMicrovascular invasion (MVI) is a significant risk factor affecting survival outcomes of patients after R0 liver resection (LR) for hepatocellular carcinoma (HCC). However, whether the existing staging systems of hepatocellular carcinoma can distinguish the prognosis of patients with MVI and the prognostic value of MVI in different subtypes of hepatocellular carcinoma remains to be clarified.MethodsA dual-center retrospective data set of 1,198 HCC patients who underwent R0 LR was included in the study between 2014 and 2016. Baseline characteristics and staging information were collected. Homogeneity and modified Akaike information criterion (AICc) were compared between each system. And the prognostic significance of MVI for overall survival (OS) was studied in each subgroup.ResultsIn the entire cohort, there were no significant survival differences between Cancer of the Liver Italian Program (CLIP) score 2 and 3 (p = 0.441), and between Taipei Integrated Scoring System (TIS) score 3 and 4 (p = 0.135). In the MVI cohort, there were no significant survival differences between Barcelona Clinic Liver Cancer stages B and C (p=0.161), CLIP scores 2 and 3 (p = 0.083), TIS scores 0 and 1 (p = 0.227), TIS scores 2 and 3 (p =0.794), Tokyo scores 3 and 4 (p=0.353), and American Joint Committee on Cancer Tumor-Node-Metastasis 7th stage I and II (p=0.151). Among the eight commonly used HCC staging systems, the Hong Kong Liver Cancer (HKLC) staging system showed the highest homogeneity and the lowest AICc value in both the entire cohort and MVI cohort. In each subgroup of the staging systems, MVI generally exhibited poor survival outcomes.ConclusionsThe HKLC staging system was the most accurate model for discriminating the prognosis of MVI patients, among the eight staging systems. Meanwhile, our findings suggest that MVI may be needed to be incorporated into the current HCC staging systems as one of the grading criteria.

Predictors of microvascular invasion in patients with hepatocellular carcinoma who are candidates for orthotopic liver transplanation

2001 ◽  
Vol 120 (5) ◽  
pp. A90-A90
Author(s):  
N ESNAOLA ◽  
G LAUWERS ◽  
N MIRZA ◽  
D NAGORNEY ◽  
D DOHERTY ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Microvascular Invasion

Prognostic value of serum osteopontin in hepatocellular carcinoma patients treated with transarterial chemoembolization

2009 ◽  
Vol 15 (3) ◽  
pp. 320 ◽  
Author(s):  
Sung Hoon Kim ◽  
Young-Hwa Chung ◽  
Soo Hyun Yang ◽  
Jeong A Kim ◽  
Myoung Kuk Jang ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Transarterial Chemoembolization ◽  
Prognostic Value
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