Dataset Information

A novel panel of biomarkers in distinction of small well-differentiated HCC from dysplastic nodules and outcome values.

ABSTRACT:

Background

Differential diagnosis of high-grade dysplastic nodules (HGDN) and well-differentiated hepatocellular carcinoma (WDHCC) represents a challenge to experienced hepatic clinicians, radiologists and hepatopathologists.

Methods

The expression profiles of aminoacylase-1 (ACY1), sequestosome-1 (SQSTM1) and glypican-3 (GPC3) in low-grade dysplastic nodules (LGDN), HGDN and WDHCC were assessed by immunohistochemistry. The differential diagnostic performances of these three markers alone and in combination for HGDN and WDHCC were investigated by logistic regression models (HGDN = 21; WDHCC = 32) and validated in an independent test set (HGDN, n = 21; WDHCC n = 24). Postoperative overall survival and time to recurrence were evaluated by univariate and multivariate analyses in an independent set of 500 patients.

Results

ACY1, SQSTM1 and GPC3 were differentially expressed in each group. For the differential diagnosis of WDHCC from HGDN, the sensitivity and specificity of the combination of ACY1?+?SQSTM1?+?GPC3 for detecting WDHCC were 93.8% and 95.2% respectively in the training set, which were higher than any of the three two-marker combinations. The validities of the four diagnostic models were further confirmed in an independent test set, and corresponding good sensitivity and specificity were observed. Interestingly, GPC3 expression in HCC tissues combined with serum ?-fetoprotein (AFP) was found to be an independent predictor for overall survival and time to recurrence.

Conclusions

ACY1 + SQSTM1 + GPC3 combination represents a potentially valuable biomarker for distinguishing between WDHCC and HGDN using immunohistochemistry. Meanwhile, low GPC3 staining combined with positive serum AFP may play a practical role in predicting poor postoperative outcome and high tumor recurrence risk.

SUBMITTER: Jin GZ

PROVIDER: S-EPMC3621586 | biostudies-literature | 2013 Mar

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A novel panel of biomarkers in distinction of small well-differentiated HCC from dysplastic nodules and outcome values.

Jin Guang-Zhi GZ Dong Hui H Yu Wen-Long WL Li Yan Y Lu Xin-Yuan XY Yu Hua H Xian Zhi-Hong ZH Dong Wei W Liu Yin-Kun YK Cong Wen-Ming WM Wu Meng-Chao MC

BMC cancer 20130327

<h4>Background</h4>Differential diagnosis of high-grade dysplastic nodules (HGDN) and well-differentiated hepatocellular carcinoma (WDHCC) represents a challenge to experienced hepatic clinicians, radiologists and hepatopathologists.<h4>Methods</h4>The expression profiles of aminoacylase-1 (ACY1), sequestosome-1 (SQSTM1) and glypican-3 (GPC3) in low-grade dysplastic nodules (LGDN), HGDN and WDHCC were assessed by immunohistochemistry. The differential diagnostic performances of these three marke ...[more]

PMID: 23537217

Similar Datasets

Project description:Hepatocellular carcinoma (HCC) is a complex disease with a multi-step carcinogenic process from preneoplastic lesions, including cirrhosis, low-grade dysplastic nodules (LGDNs), and high-grade dysplastic nodules (HGDNs) to HCC. There is only an elemental understanding of its molecular pathogenesis, for which a key problem is to identify when and how the critical transition happens during the HCC initiation period at a molecular level. In this work, for the first time, we revealed that LGDNs is the tipping point (i.e., pre-HCC state rather than HCC state) of hepatocarcinogenesis based on a series of gene expression profiles by a new mathematical model termed dynamic network biomarkers (DNB)-a group of dominant genes or molecules for the transition. Different from the conventional biomarkers based on the differential expressions of the observed genes (or molecules) for diagnosing a disease state, the DNB model exploits collective fluctuations and correlations of the observed genes, thereby predicting the imminent disease state or diagnosing the critical state. Our results show that DNB composed of 59 genes signals the tipping point of HCC (i.e., LGDNs). On the other hand, there are a large number of differentially expressed genes between cirrhosis and HGDNs, which highlighted the stark differences or drastic changes before and after the tipping point or LGDNs, implying the 59 DNB members serving as the early-warning signals of the upcoming drastic deterioration for HCC. We further identified the biological pathways responsible for this transition, such as the type I interferon signaling pathway, Janus kinase-signal transducers and activators of transcription (JAK-STAT) signaling pathway, transforming growth factor (TGF)-? signaling pathway, retinoic acid-inducible gene I (RIG-I)-like receptor signaling pathway, cell adhesion molecules, and cell cycle. In particular, pathways related to immune system reactions and cell adhesion were downregulated, and pathways related to cell growth and death were upregulated. Furthermore, DNB was validated as an effective predictor of prognosis for HCV-induced HCC patients by survival analysis on independent data, suggesting a potential clinical application of DNB. This work provides biological insights into the dynamic regulations of the critical transitions during multistep hepatocarcinogenesis.

Project description:Objective: To report the rate of candidate actionable somatic mutations in patients with locally advanced and metastatic gastro-enteropancreatic (GEP) neuroendocrine tumors (NET) and of other genetic alterations that may be associated with tumorigenesis. Methods: A phase II mutation targeted therapy trial was conducted in patients with advanced well-differentiated G1/G2 GEP-NET. Mutations found in the mTOR pathway-associated genes led to treatment with the mTOR inhibitor everolimus, and were defined as actionable. Tumor deoxyribonucleic acid (DNA) from GEP-NET were sequenced and compared with germline DNA, using the OncoVAR-NET assay, designed for hybrid capture sequencing of 500 tumor suppressor genes and oncogenes. Somatic variants were called and copy-number (CN) variant analysis was performed. Results: Thirty patients (14 small-intestine, 8 pancreatic, 3 unknown primary NET, and 5 of other primary sites) harbored 37 lesions (4 patients had DNA of multiple lesions sequenced). Only 2 patients with sporadic NET (n = 26) had an actionable mutation leading to treatment with everolimus. Driver somatic mutations were detected in 18 of 30 patients (21/37 lesions sequenced). In the remaining samples without a driver mutation, CN alterations were found in 11/16 tumors (10/12 patients), including CN loss of chromosome (Chr) 18 (P<.05), CN gain of Chr 5, and loss of Chr 13. CN losses in Chr 18 were more common in patients without driver mutations detected. Pronounced genetic heterogeneity was detected in patients with multiple lesions sequenced. Conclusion: Genome-wide DNA sequencing may identify candidate actionable genes and lead to the identification of novel target genes for advanced well-differentiated GEP-NET. Abbreviations: Chr = chromosome; CN = copy number; DNA = deoxyribonucleic acid; FDA = Food and Drug Administration; GEP = gastro-enteropancreatic; MEN-1 = multiple endocrine neoplasia syndrome type 1; mTOR = mammalian target of rapamycin; NET = neuroendocrine tumor; PFS = progression-free survival; PNET = pancreatic neuroendocrine tumors; SINET = small-intestine neuroendocrine tumor.

Dataset Information

A novel panel of biomarkers in distinction of small well-differentiated HCC from dysplastic nodules and outcome values.

Background

Methods

Results

Conclusions

Publications

A novel panel of biomarkers in distinction of small well-differentiated HCC from dysplastic nodules and outcome values.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure