Dataset Information

The Relationship Between Serum Interleukin-6 and the Recurrence of Hepatitis B Virus Related Hepatocellular Carcinoma after Curative Resection.

ABSTRACT: The aim of this study is to assess whether preoperative serum interleukin-6 (IL-6) can predict recurrence of hepatitis B virus (HBV)-associated hepatocellular carcinoma (HCC). The association between preoperative IL-6 levels and HCC recurrence following curative hepatectomy in 146 patients with chronic HBV infection was determined. Patients were divided into groups based on the presence or absence of HCC recurrence. Serum IL-6 levels were compared between groups, and the association between serum IL-6 level and greatest tumor dimension was also analyzed. Receiver operating characteristics (ROC) curve was used to define the optimal cutoff value for predicting recurrence-free survival (RFS) and overall survival (OS) rates. The OS and RFS rates were calculated using the Kaplan-Meier method. Out of 146 patients, 80 (54.8%) patients were documented as having HCC recurrence during the follow-up period. After adjusting for potential confounders, serum IL-6 levels were significantly associated with HCC recurrence, and a saturation effect existed with serum IL-6 levels up to 3.7 pg/mL. In addition, patients with preoperative serum IL-6 levels over 3.1 pg/mL had lower RFS and OS rates (P < 0.01). There was no significant correlation between preoperative serum IL-6 levels and maximal tumor dimension (r = 0.0003, P = 0.84). Elevated serum levels of IL-6 were significantly associated with an increased risk of HBV-associated HCC recurrence suggesting that preoperative IL-6 serum level is potential biomarker for early prediction of HBV-associated HCC recurrence.

SUBMITTER: Sheng T

PROVIDER: S-EPMC4616529 | biostudies-other | 2015 Jun

REPOSITORIES: biostudies-other

ACCESS DATA

Similar Datasets

Project description:BackgroundDespite the recent identification of several prognostic gene signatures, the lack of common genes among experimental cohorts has posed a considerable challenge in uncovering the molecular basis underlying hepatocellular carcinoma (HCC) recurrence for application in clinical purposes. To overcome the limitations of individual gene-based analysis, we applied a pathway-based approach for analysis of HCC recurrence.ResultsBy implementing a permutation-based semi-supervised principal component analysis algorithm using the optimal principal component, we selected sixty-four pathways associated with hepatitis B virus (HBV)-positive HCC recurrence (p < 0.01), from our microarray dataset composed of 142 HBV-positive HCCs. In relation to the public HBV- and public hepatitis C virus (HCV)-positive HCC datasets, we detected 46 (71.9%) and 18 (28.1%) common recurrence-associated pathways, respectively. However, overlap of recurrence-associated genes between datasets was rare, further supporting the utility of the pathway-based approach for recurrence analysis between different HCC datasets. Non-supervised clustering of the 64 recurrence-associated pathways facilitated the classification of HCC patients into high- and low-risk subgroups, based on risk of recurrence (p < 0.0001). The pathways identified were additionally successfully applied to discriminate subgroups depending on recurrence risk within the public HCC datasets. Through multivariate analysis, these recurrence-associated pathways were identified as an independent prognostic factor (p < 0.0001) along with tumor number, tumor size and Edmondson's grade. Moreover, the pathway-based approach had a clinical advantage in terms of discriminating the high-risk subgroup (N = 12) among patients (N = 26) with small HCC (<3 cm).ConclusionsUsing pathway-based analysis, we successfully identified the pathways involved in recurrence of HBV-positive HCC that may be effectively used as prognostic markers.

Dataset Information

The Relationship Between Serum Interleukin-6 and the Recurrence of Hepatitis B Virus Related Hepatocellular Carcinoma after Curative Resection.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets