Dataset Information

Apolipoprotein A1: a novel serum biomarker for predicting the prognosis of hepatocellular carcinoma after curative resection.

ABSTRACT: As a major protein constituent of high density lipoprotein, Apolipoprotein A1 (ApoA-1) might be associated with cancer progression. Our study investigated the serum ApoA-1 level for the prognosis of 443 patients with hepatocellular carcinoma (HCC) and its effects on tumor cells. We found that the serum ApoA-1 level was significantly lower in HCC patients with tumor recurrence, and was an independent indicator of tumor-free survival and overall survival. Low serum ApoA-1 levels were significantly associated with multiple tumors and high Barcelona Clinic Liver Cancer stage. The circulating tumor cell (CTC) levels were significantly higher in patients with low serum ApoA-1 compared with those with high serum ApoA-1 levels (4.03 ± 0.98 vs. 1.48 ± 0.22; p=0.001). In patients with detectable CTCs, those with low ApoA-1 levels had higher recurrence rates and shorter survival times. In vitro experiments showed that ApoA-1 can inhibit tumor cell proliferation through cell cycle arrest and promote apoptosis through down regulating mitogen-activated protein kinase (MAPK) pathway. In addition, ApoA-1 might impair extracellular matrix degradation properties of tumor cells. Taken together, our findings indicate that decreased serum ApoA-1 levels are a novel prognostic factor for HCC, and the role of ApoA-1 in inhibition of proliferation and promotion of apoptosis for tumor cells during their hematogenous dissemination are presumably responsible for the poor prognosis of patients with low ApoA-1 levels. Furthermore, AopA-1 might be a promising therapeutic target to reduce recurrence and metastasis for HCC patients after resection.

SUBMITTER: Ma XL

PROVIDER: S-EPMC5342581 | biostudies-literature | 2016 Oct

REPOSITORIES: biostudies-literature

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Apolipoprotein A1: a novel serum biomarker for predicting the prognosis of hepatocellular carcinoma after curative resection.

Ma Xiao-Lu XL Gao Xing-Hui XH Gong Zi-Jun ZJ Wu Jiong J Tian Lu L Zhang Chun-Yan CY Zhou Yan Y Sun Yun-Fan YF Hu Bo B Qiu Shuang-Jian SJ Zhou Jian J Fan Jia J Guo Wei W Yang Xin-Rong XR

Oncotarget 20161001 43

As a major protein constituent of high density lipoprotein, Apolipoprotein A1 (ApoA-1) might be associated with cancer progression. Our study investigated the serum ApoA-1 level for the prognosis of 443 patients with hepatocellular carcinoma (HCC) and its effects on tumor cells. We found that the serum ApoA-1 level was significantly lower in HCC patients with tumor recurrence, and was an independent indicator of tumor-free survival and overall survival. Low serum ApoA-1 levels were significantly ...[more]

PMID: 27683106

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Project description:BACKGROUND: Surgical resection is one important curative treatment for hepatocellular carcinoma (HCC), but the prognosis following surgery differs substantially and such large variation is mainly unexplained. A review of the literature yields a number of clinicopathologic parameters associated with HCC prognosis. However, the results are not consistent due to lack of systemic approach to establish a prediction model incorporating all these parameters. METHODS: We conducted a retrospective analysis on the common clinicopathologic parameters from a cohort of 572 ethnic Chinese HCC patients who received curative surgery. The cases were randomly divided into training (n = 272) and validation (n = 300) sets. Each parameter was individually tested and the significant parameters were entered into a linear classifier for model building, and the prediction accuracy was assessed in the validation set RESULTS: Our findings based on the training set data reveal 6 common clinicopathologic parameters (tumor size, number of tumor nodules, tumor stage, venous infiltration status, and serum alpha-fetoprotein and total albumin levels) that were significantly associated with the overall HCC survival and disease-free survival (time to recurrence). We next built a linear classifier model by multivariate Cox regression to predict prognostic outcomes of HCC patients after curative surgery This analysis detected a considerable fraction of variance in HCC prognosis and the area under the ROC curve was about 70%. We further evaluated the model using two other protocols; leave-one-out procedure (n = 264) and independent validation (n = 300). Both were found to have excellent prediction power. The predicted score could separate patients into distinct groups with respect to survival (p-value = 1.8e-12) and disease free survival (p-value = 3.2e-7). CONCLUSION: This described model will provide valuable guidance on prognosis after curative surgery for HCC in clinical practice. The adaptive nature allows easy accommodation for future new biomarker inputs, and it may serve as the foundation for future modeling and prediction for HCC prognosis after surgical treatment.

Project description:Purpose:Prognostic prediction after curative resection of primary hepatocellular carcinoma (PHCC) remains an arduous task. The S-index calculated from ?-glutamyl transpeptidase, albumin, and platelets is reported to predict the severity of liver fibrosis. We constructed a nomogram for predicting the survival probability of PHCC based on a new indicator, the S-index, combined with other routine clinical parameters. Patients and methods:We selected 490 patients with PHCC postradical surgery at the First Affiliated Hospital of Wenzhou Medical University between January 2007 and January 2014. The subjects were randomly allocated into the training cohort and the validation cohort in the ratio 7:3 by the digital method. Important variables screened by univariate analysis were included in multivariate analysis to obtain independent risk factors for predicting the prognosis of PHCC. The construction of the nomogram was based on Cox proportional hazard regression models. The concordance index (C-index) was used in the nomogram for evaluating the model performance for prognosis. We drew time-dependent receiver operating characteristic curves to compare our model with other staging systems. Results:The nomogram based on six independent risk factors after multivariate analyses had good predictive power after radical surgery of PHCC. In the training and validation groups, the C-index of the nomogram was highly consistent for evaluating survival from PHCC. Compared with the traditional scoring system, the areas under time-dependent receiver operating characteristic curves were 0.7382, 0.7293, and 0.7520 for 1-, 3-, and 5-year overall survival, respectively. In summary, the nomogram showed excellent results in terms of prognosis of PHCC. Conclusion:Based on the S-index and the other clinical indicators, we developed a precise nomogram that predicts the survival probability of patients with PHCC after radical surgery. This tool can provide effective information for surgeons and patients.

Dataset Information

Apolipoprotein A1: a novel serum biomarker for predicting the prognosis of hepatocellular carcinoma after curative resection.

Publications

Apolipoprotein A1: a novel serum biomarker for predicting the prognosis of hepatocellular carcinoma after curative resection.

Similar Datasets

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