Dataset Information

Peritumoral EpCAM Is an Independent Prognostic Marker after Curative Resection of HBV-Related Hepatocellular Carcinoma.

ABSTRACT: Accumulating evidence suggests that the tumor microenvironment has a profound influence on tumor initiation and progression, opening a new avenue for studying tumor biology. Nonetheless, the prognostic values of the peritumoral expression of EpCAM and CD13 remain to be elucidated in hepatocellular carcinoma (HCC) patients. In this study, the expression of EpCAM and CD13 was assessed by immunohistochemistry in peritumoral liver hepatocytes from 106 hepatitis B virus- (HBV-) related HCC patients who had undergone curative hepatectomy. The peritumoral EpCAM-positive group had a significantly worse overall survival (OS) (p = 0.003) and recurrence-free survival (RFS) (p = 0.022) compared to the negative group. Peritumoral CD13-positive patients were also associated with poor OS (p = 0.038), while not significantly associated with RFS. The adjusted multivariate COX proportional hazard regression analysis suggested that only the positive expression of peritumoral EpCAM precisely predicted poor OS. Being peritumoral EpCAM positive was also significantly associated with a larger tumor size, liver cirrhosis, and more frequent vascular invasion; however, no statistically significant association was observed between CD13 and any clinicopathological features. Taken together, peritumoral EpCAM and CD13 expression was associated with a poor prognosis, but EpCAM may be a better prognostic marker than CD13 in HBV-related HCC patients. In the future, peritumoral EpCAM could be a good target for adjuvant therapy after curative hepatectomy.

SUBMITTER: Dai XM

PROVIDER: S-EPMC5442434 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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Peritumoral EpCAM Is an Independent Prognostic Marker after Curative Resection of HBV-Related Hepatocellular Carcinoma.

Dai Xiao-Meng XM Huang Tao T Yang Sheng-Li SL Zheng Xiu-Mei XM Chen George G GG Zhang Tao T

Disease markers 20170510

Accumulating evidence suggests that the tumor microenvironment has a profound influence on tumor initiation and progression, opening a new avenue for studying tumor biology. Nonetheless, the prognostic values of the peritumoral expression of EpCAM and CD13 remain to be elucidated in hepatocellular carcinoma (HCC) patients. In this study, the expression of EpCAM and CD13 was assessed by immunohistochemistry in peritumoral liver hepatocytes from 106 hepatitis B virus- (HBV-) related HCC patients w ...[more]

PMID: 28572700

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Project description:OBJECTIVE:To construct a prediction model based on peritumoral radiomics signatures from CT images and investigate its efficiency in predicting early recurrence (ER) of hepatocellular carcinoma (HCC) after curative treatment. MATERIALS AND METHODS:In total, 156 patients with primary HCC were randomly divided into the training cohort (109 patients) and the validation cohort (47 patients). From the pretreatment CT images, we extracted 3-phase two-dimensional images from the largest cross-sectional area of the tumor. A region of interest (ROI) was manually delineated around the lesion for tumoral radiomics (T-RO) feature extraction, and another ROI was outlined with an additional 2 cm peritumoral area for peritumoral radiomics (PT-RO) feature extraction. The least absolute shrinkage and selection operator (LASSO) logistic regression model was applied for feature selection and model construction. The T-RO and PT-RO models were constructed. In the validation cohort, the prediction efficiencies of the two models and peritumoral enhancement (PT-E) were evaluated qualitatively by receiver operating characteristic (ROC) curves, calibration curves and decision curves and quantitatively by area under the curve (AUC), the category-free net reclassification index (cfNRI) and integrated discrimination improvement values (IDI). RESULTS:By comparing AUC values, the prediction accuracy in the validation cohort was good for the PT-RO model (0.80 vs. 0.79, P = 0.47) but poor for the T-RO model (0.82 vs. 0.62, P < 0.01), which was significantly overfitted. In the validation cohort, the ROC curves, calibration curves and decision curves indicated that the PT-RO model had better calibration efficiency and provided greater clinical benefits. CfNRI indicated that the PT-RO model correctly reclassified 47% of ER patients and 32% of non-ER patients compared to the T-RO model (P < 0.01); additionally, the PT-RO model correctly reclassified 24% of ER patients and 41% of non-ER patients compared to PT-E (P = 0.02). IDI indicated that the PT-RO model could improve prediction accuracy by 0.22 (P < 0.01) compared to the T-RO model and by 0.20 (P = 0.01) compared to PT-E. CONCLUSION:The CT-based PT-RO model can effectively predict the ER of HCC and is more efficient than the T-RO model and the conventional imaging feature PT-E.

Dataset Information

Peritumoral EpCAM Is an Independent Prognostic Marker after Curative Resection of HBV-Related Hepatocellular Carcinoma.

Publications

Peritumoral EpCAM Is an Independent Prognostic Marker after Curative Resection of HBV-Related Hepatocellular Carcinoma.

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