Literature DB >> 18377418

Translational microarray systems for outcome prediction of hepatocellular carcinoma.

Norio Iizuka1, Yoshihiko Hamamoto, Ryouichi Tsunedomi, Masaaki Oka.   

Abstract

DNA microarray technology has revolutionized our understanding of the molecular basis of hepatocellular carcinoma (HCC), one of the most fatal human cancers with a high recurrence rate. Many researchers have used DNA microarray technology to reclassify HCC with respect to metastatic potential and to develop predictors for the outcome of HCC. However, developed predictors have reached the level only of small retrospective studies, and their current status is far from that required for clinical use. This is due to the lack of transparent data, the high cost and data instability associated with the high dimensionality of the technique, the infancy of bioinformatics, and the complicated nature of recurrent HCC. This comprehensive review summarizes: (i) class comparison studies to identify genes or pathways involved in HCC metastasis (ii) class discovery studies that have resulted in the identification of a new molecular subclass of HCC with respect to metastasis, and (iii) class prediction studies to develop multidimensional predictors for HCC outcome. We also discuss issues that need to be addressed so that the power of array-based predictors can be estimated prospectively in large independent cohorts of HCC patients.

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Year:  2008        PMID: 18377418     DOI: 10.1111/j.1349-7006.2008.00751.x

Source DB:  PubMed          Journal:  Cancer Sci        ISSN: 1347-9032            Impact factor:   6.716


  9 in total

1.  Integrative genomics: liver regeneration and hepatocellular carcinoma.

Authors:  Zeynep Coban; Michelle Craig Barton
Journal:  J Cell Biochem       Date:  2012-07       Impact factor: 4.429

Review 2.  Molecular signatures of noncancerous liver tissue can predict the risk for late recurrence of hepatocellular carcinoma.

Authors:  Tohru Utsunomiya; Mitsuo Shimada; Satoru Imura; Yuji Morine; Tetsuya Ikemoto; Masaki Mori
Journal:  J Gastroenterol       Date:  2009-12-08       Impact factor: 7.527

3.  Fructose-Bisphosphate Aldolase A Regulates Hypoxic Adaptation in Hepatocellular Carcinoma and Involved with Tumor Malignancy.

Authors:  Xin Li; Fengxing Jiang; Zhong Ge; Bin Chen; Jiang Yu; Mingjun Xin; Jiandong Wang; Lingxuan An; Jichao Wei; Liqun Wu
Journal:  Dig Dis Sci       Date:  2019-04-30       Impact factor: 3.199

Review 4.  Gene signatures in hepatocellular carcinoma (HCC).

Authors:  Ourania M Andrisani; Leo Studach; Philippe Merle
Journal:  Semin Cancer Biol       Date:  2010-09-17       Impact factor: 15.707

5.  Distinct expression patterns in hepatitis B virus- and hepatitis C virus-infected hepatocellular carcinoma.

Authors:  Chun-Feng Lee; Zhi-Qiang Ling; Ting Zhao; Kuan-Rong Lee
Journal:  World J Gastroenterol       Date:  2008-10-21       Impact factor: 5.742

6.  Dysfunctional activation of neurotensin/IL-8 pathway in hepatocellular carcinoma is associated with increased inflammatory response in microenvironment, more epithelial mesenchymal transition in cancer and worse prognosis in patients.

Authors:  Jinpu Yu; Xiubao Ren; Yongzi Chen; Pengpeng Liu; Xiyin Wei; Hui Li; Guoguang Ying; Kexin Chen; Hans Winkler; Xishan Hao
Journal:  PLoS One       Date:  2013-02-13       Impact factor: 3.240

7.  Microarray-based gene expression analysis of hepatocellular carcinoma.

Authors:  Thorsten Maass; Ioannis Sfakianakis; Frank Staib; Markus Krupp; Peter R Galle; Andreas Teufel
Journal:  Curr Genomics       Date:  2010-06       Impact factor: 2.236

8.  High expression of ribonucleotide reductase subunit M2 correlates with poor prognosis of hepatocellular carcinoma.

Authors:  Boin Lee; Sang Yun Ha; Dae Hyun Song; Hyun Woo Lee; Soo Youn Cho; Cheol-Keun Park
Journal:  Gut Liver       Date:  2014-11-15       Impact factor: 4.519

9.  Prediction of Early Recurrence of Liver Cancer by a Novel Discrete Bayes Decision Rule for Personalized Medicine.

Authors:  Hiroyuki Ogihara; Norio Iizuka; Yoshihiko Hamamoto
Journal:  Biomed Res Int       Date:  2016-10-09       Impact factor: 3.411

  9 in total

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