Nature Medicine9, 416 - 423 (2003)
Published online: 17 March 2003; | doi:10.1038/nm843
Predicting hepatitis B virus−positive metastatic hepatocellular carcinomas using gene expression profiling and supervised machine learning
Qing-Hai Ye1, Lun-Xiu Qin1, Marshonna Forgues2, Ping He2, Jin Woo Kim2, Amy C. Peng3, 4, Richard Simon3, Yan Li1, Ana I. Robles2, Yidong Chen5, Zeng-Chen Ma1, Zhi-Quan Wu1, Sheng-Long Ye1, Yin-Kun Liu1, Zhao-You Tang1
& Xin Wei Wang2
1
Liver Cancer Institute and Zhongshan Hospital, Fudan University, Shanghai, China
2
Laboratory of Human Carcinogenesis, Center for Cancer Research, National Cancer Institute, Bethesda, Maryland, USA
3
Biometrics Research Branch, National Cancer Institute, Rockville, Maryland, USA
4
EMMES Corp., Rockville, Maryland, USA
5
Laboratory of Cancer Genetics, National Human Genome Research Institute, Bethesda, Maryland, USA
Correspondence should be addressed to Xin Wei Wang xw3u@nih.gov
Hepatocellular carcinoma (HCC) is one of the most common and aggressive human malignancies. Its high mortality rate is mainly a result of intra-hepatic metastases. We analyzed the expression profiles of HCC samples without or with intra-hepatic metastases. Using a supervised machine-learning algorithm, we generated for the first time a molecular signature that can classify metastatic HCC patients and identified genes that were relevant to metastasis and patient survival. We found that the gene expression signature of primary HCCs with accompanying metastasis was very similar to that of their corresponding metastases, implying that genes favoring metastasis progression were initiated in the primary tumors. Osteopontin, which was identified as a lead gene in the signature, was over-expressed in metastatic HCC; an osteopontin-specific antibody effectively blocked HCC cell invasion in vitro and inhibited pulmonary metastasis of HCC cells in nude mice. Thus, osteopontin acts as both a diagnostic marker and a potential therapeutic target for metastatic HCC.
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