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A unique metastasis gene signature enables prediction of tumor relapse in early-stage hepatocellular carcinoma patients.

ABSTRACT: Metastasis-related recurrence often occurs in hepatocellular carcinoma (HCC) patients who receive curative therapies. At present, it is challenging to identify patients with high risk of recurrence, which would warrant additional therapies. In this study, we sought to analyze a recently developed metastasis-related gene signature for its utility in predicting HCC survival, using 2 independent cohorts consisting of a total of 386 patients who received radical resection. Cohort 1 contained 247 predominantly HBV-positive cases analyzed with an Affymetrix platform, whereas cohort 2 contained 139 cases with mixed etiology analyzed with the NCI Oligo Set microarray platform. We employed a survival risk prediction algorithm with training, test, and independent cross-validation strategies and found that the gene signature is predictive of overall and disease-free survival. Importantly, risk was significantly predicted independently of clinical characteristics and microarray platform. In addition, survival prediction was successful in patients with early disease, such as small (<5 cm in diameter) and solitary tumors, and the signature predicted particularly well for early recurrence risk (<2 years), especially when combined with serum alpha fetoprotein or tumor staging. In conclusion, we have shown in 2 independent cohorts with mixed etiologies and ethnicity that the metastasis gene signature is a useful tool to predict HCC outcome, suggesting the general utility of this classifier. We recommend the use of this classifier as a molecular diagnostic test to assess the risk that an HCC patient will develop tumor relapse within 2 years after surgical resection, particularly for those with early-stage tumors and solitary presentation.

SUBMITTER: Roessler S

PROVIDER: S-EPMC3064515 | biostudies-literature | 2010 Dec

REPOSITORIES: biostudies-literature

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A unique metastasis gene signature enables prediction of tumor relapse in early-stage hepatocellular carcinoma patients.

Roessler Stephanie S Jia Hu-Liang HL Budhu Anuradha A Forgues Marshonna M Ye Qing-Hai QH Lee Ju-Seog JS Thorgeirsson Snorri S SS Sun Zhongtang Z Tang Zhao-You ZY Qin Lun-Xiu LX Wang Xin Wei XW

Cancer research 20101201 24

Metastasis-related recurrence often occurs in hepatocellular carcinoma (HCC) patients who receive curative therapies. At present, it is challenging to identify patients with high risk of recurrence, which would warrant additional therapies. In this study, we sought to analyze a recently developed metastasis-related gene signature for its utility in predicting HCC survival, using 2 independent cohorts consisting of a total of 386 patients who received radical resection. Cohort 1 contained 247 pre ...[more]

PMID: 21159642

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Project description:BackgroundLocal relapses and metastases are primary causes of death in lung cancer patients. In the present study, we aimed to develop a prognostic signature based on metastasis-associated lncRNAs in patients with lung adenocarcinoma (LUAD).MethodsFirstly, the potential metastasis-associated lncRNAs were identified by analyzing high-throughput data from The Cancer Genome Atlas (TCGA), and based on which, an lncRNA signature was constructed for prediction of relapse in LUAD patients using Cox proportional hazards regression analysis. Moreover, the prognostic performance of the lncRNA signature was evaluated using Kaplan-Meier survival analysis, time-dependent receiver operating characteristic (ROC) curve and Cox analysis, respectively. In addition, the potential metastasis-associated function of these six lncRNAs was confirmed by lncRNA over-expression or depletion and in vitro transwell assays in LUAD cells.ResultsAn lncRNA signature consisting of six most important prognostic factors (LINC01819, ZNF649-AS1, HNF4A-AS1, FAM222A-AS1, LINC02323 and LINC00672) was developed. The signature was an independent predictor for patients' relapse-free survival (RFS), which could provide higher tumor relapse prediction capability compared with the TNM staging system at three years and five years, respectively (P = 0.0209 and P = 0.0468). Furthermore, the combination of this lncRNA signature and TNM stage had better prognostic value than TNM stage alone at three and five years, respectively (P = 0.0006 and P = 0.0096). Additionally, all the lncRNAs of the signature had a regulatory role in the LUAD cell mobility.ConclusionsThis novel six-lncRNA signature had considerable prognostic value for prediction of relapse in LUAD patients.Key pointsSignificant findings of the study The unique metastasis-associated lncRNA signature was related to tumor metastasis and prognosis in LUAD patients. What this study adds This signature had considerable prognostic value for prediction of relapse in LUAD patients.

Project description:BackgroundThe incidence of hepatocellular carcinoma (HCC) is rising worldwide, and there is limited therapeutic efficacy due to tumor microenvironment heterogeneity and difficulty in early-stage screening. This study aimed to develop and validate a gene set-based signature for early-stage HCC (eHCC) patients and further explored specific marker dysregulation mechanisms as well as immune characteristics.MethodsWe performed an integrated bioinformatics analysis of genomic, transcriptomic, and clinical data with three independent cohorts. We systematically reviewed the crosstalk between specific genes, tumor prognosis, immune characteristics, and biological function in the different pathological stage samples. Univariate and multivariate survival analyses were performed in The Cancer Genome Atlas (TCGA) patients with survival data. Diethylnitrosamine (DEN)-induced HCC in Wistar rats was employed to verify the reliability of the predictions.ResultsWe identified a Cluster gene that potentially segregates patients with eHCC from non-tumor, through integrated analysis of expression, overall survival, immune cell characteristics, and biology function landscapes. Immune infiltration analysis showed that lower infiltration of specific immune cells may be responsible for significantly worse prognosis in HCC (hazard ratio, 1.691; 95% CI: 1.171-2.441; p = 0.012), such as CD8 Tem and cytotoxic T cells (CTLs) in eHCC. Our results identified that Cluster C1 signature presented a high accuracy in predicting CD8 Tem and CTL immune cells (receiver operating characteristic (ROC) = 0.647) and cancerization (ROC = 0.946) in liver. As a central member of Cluster C1, overexpressed PRKDC was associated with the higher genetic alteration in eHCC than advanced-stage HCC (aHCC), which was also connected to immune cell-related poor prognosis. Finally, the predictive outcome of Cluster C1 and PRKDC alteration in DEN-induced eHCC rats was also confirmed.ConclusionsAs a tumor prognosis-relevant gene set-based signature, Cluster C1 showed an effective approach to predict cancerization of eHCC and its related immune characteristics with considerable clinical value.

Project description:BackgroundLiver cirrhosis is one of the major drivers of hepatocellular carcinoma (HCC). In the present study, we aimed to identify and validate new biomarker for early prediction of HCC development in early-stage cirrhosis patients.MethodsmRNA expression and clinical parameters of GSE63898, GSE89377, GSE15654, GSE14520, and TCGA-HCC cohort and ICGC-HCC cohort were downloaded for analysis. Wilcoxon test was performed to identify DEGs. Univariate and multivariate Cox regression analysis were used to develop the risk signature, and ROC analysis was performed to analyze the predictive accuracy and sensitivity of the risk signature.ResultsThere were 42 DEGs (including 28 upregulated genes and 14 downregulated genes) found in early-stage liver cirrhosis patients before developing HCC from GSE1565442. Then, a risk signature consisting of 8 DEGs could effectively classify early-stage cirrhosis patients into high-risk group with shorter HCC development time and low-risk group with longer HCC development time from GSE15654. Multivariate Cox analysis indicated that the risk signature was an independent prognostic factor for the prediction of HCC development and ROC analysis showed that the signature exhibited good predictive efficiency in predicting 2-, 5-, and 10-year HCC development. Mechanistically, significantly higher proportions of CD8 T cells were found to be enriched in cirrhosis patients with low risk score, and higher CD8 T cells were associated with longer HCC development time. Besides, the signature was an independent prognostic factor for poorer prognosis of early-stage liver cirrhosis patients of GSE15654. Moreover, the signature could also separate HCC patients from healthy controls and was also associated with the poorer prognosis of HCC patients from three HCC cohorts. Finally, we also identified HDAC inhibitors, such as trichostatin A, to be a potential chemopreventive treatment for the prevention of HCC development by targeting risk signature based on CMap analysis.ConclusionA risk signature was developed and validated for early prediction of HCC development, which may be a useful tool to set up individualized follow-up interval schedules.

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A unique metastasis gene signature enables prediction of tumor relapse in early-stage hepatocellular carcinoma patients.

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A unique metastasis gene signature enables prediction of tumor relapse in early-stage hepatocellular carcinoma patients.

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