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Article: Clinicopathologic and gene expression parameters predict liver cancer prognosis

TitleClinicopathologic and gene expression parameters predict liver cancer prognosis
Authors
Issue Date2011
PublisherBioMed Central Ltd. The Journal's web site is located at http://www.biomedcentral.com/bmccancer/
Citation
Bmc Cancer, 2011, v. 11 How to Cite?
AbstractBackground: The prognosis of hepatocellular carcinoma (HCC) varies following surgical resection and the large variation remains largely unexplained. Studies have revealed the ability of clinicopathologic parameters and gene expression to predict HCC prognosis. However, there has been little systematic effort to compare the performance of these two types of predictors or combine them in a comprehensive model.Methods: Tumor and adjacent non-tumor liver tissues were collected from 272 ethnic Chinese HCC patients who received curative surgery. We combined clinicopathologic parameters and gene expression data (from both tissue types) in predicting HCC prognosis. Cross-validation and independent studies were employed to assess prediction.Results: HCC prognosis was significantly associated with six clinicopathologic parameters, which can partition the patients into good- and poor-prognosis groups. Within each group, gene expression data further divide patients into distinct prognostic subgroups. Our predictive genes significantly overlap with previously published gene sets predictive of prognosis. Moreover, the predictive genes were enriched for genes that underwent normal-to-tumor gene network transformation. Previously documented liver eSNPs underlying the HCC predictive gene signatures were enriched for SNPs that associated with HCC prognosis, providing support that these genes are involved in key processes of tumorigenesis.Conclusion: When applied individually, clinicopathologic parameters and gene expression offered similar predictive power for HCC prognosis. In contrast, a combination of the two types of data dramatically improved the power to predict HCC prognosis. Our results also provided a framework for understanding the impact of gene expression on the processes of tumorigenesis and clinical outcome. © 2011 Hao et al; licensee BioMed Central Ltd.
Persistent Identifierhttp://hdl.handle.net/10722/148658
ISSN
2014 Impact Factor: 3.362
2014 SCImago Journal Rankings: 1.403
PubMed Central ID
ISI Accession Number ID
Funding AgencyGrant Number
Research Grants Council of Hong Kong
Hong Kong Government
Funding Information:

The work was supported by Research Grants Council of Hong Kong and Innovation and Technology Fund of the Hong Kong Government to J.M.L. We would like to thank for the technical supports from Ashley Wong and Kit-Yuk Mak of the Queen Mary Hospital. IOL Ng is a Loke Yew Professor in Pathology.

References

 

DC FieldValueLanguage
dc.contributor.authorHao, Ken_HK
dc.contributor.authorLamb, Jen_HK
dc.contributor.authorZhang, Cen_HK
dc.contributor.authorXie, Ten_HK
dc.contributor.authorWang, Ken_HK
dc.contributor.authorZhang, Ben_HK
dc.contributor.authorChudin, Een_HK
dc.contributor.authorLee, NPen_HK
dc.contributor.authorMao, Men_HK
dc.contributor.authorZhong, Hen_HK
dc.contributor.authorGreenawalt, Den_HK
dc.contributor.authorFerguson, MDen_HK
dc.contributor.authorNg, IOen_HK
dc.contributor.authorSham, PCen_HK
dc.contributor.authorPoon, RTen_HK
dc.contributor.authorMolony, Cen_HK
dc.contributor.authorSchadt, EEen_HK
dc.contributor.authorDai, Hen_HK
dc.contributor.authorLuk, JMen_HK
dc.date.accessioned2012-05-29T06:14:26Z-
dc.date.available2012-05-29T06:14:26Z-
dc.date.issued2011en_HK
dc.identifier.citationBmc Cancer, 2011, v. 11en_HK
dc.identifier.issn1471-2407en_HK
dc.identifier.urihttp://hdl.handle.net/10722/148658-
dc.description.abstractBackground: The prognosis of hepatocellular carcinoma (HCC) varies following surgical resection and the large variation remains largely unexplained. Studies have revealed the ability of clinicopathologic parameters and gene expression to predict HCC prognosis. However, there has been little systematic effort to compare the performance of these two types of predictors or combine them in a comprehensive model.Methods: Tumor and adjacent non-tumor liver tissues were collected from 272 ethnic Chinese HCC patients who received curative surgery. We combined clinicopathologic parameters and gene expression data (from both tissue types) in predicting HCC prognosis. Cross-validation and independent studies were employed to assess prediction.Results: HCC prognosis was significantly associated with six clinicopathologic parameters, which can partition the patients into good- and poor-prognosis groups. Within each group, gene expression data further divide patients into distinct prognostic subgroups. Our predictive genes significantly overlap with previously published gene sets predictive of prognosis. Moreover, the predictive genes were enriched for genes that underwent normal-to-tumor gene network transformation. Previously documented liver eSNPs underlying the HCC predictive gene signatures were enriched for SNPs that associated with HCC prognosis, providing support that these genes are involved in key processes of tumorigenesis.Conclusion: When applied individually, clinicopathologic parameters and gene expression offered similar predictive power for HCC prognosis. In contrast, a combination of the two types of data dramatically improved the power to predict HCC prognosis. Our results also provided a framework for understanding the impact of gene expression on the processes of tumorigenesis and clinical outcome. © 2011 Hao et al; licensee BioMed Central Ltd.en_HK
dc.languageengen_US
dc.publisherBioMed Central Ltd. The Journal's web site is located at http://www.biomedcentral.com/bmccancer/en_HK
dc.relation.ispartofBMC Canceren_HK
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.titleClinicopathologic and gene expression parameters predict liver cancer prognosisen_HK
dc.typeArticleen_HK
dc.identifier.emailLee, NP: nikkilee@hku.hken_HK
dc.identifier.emailNg, IO: iolng@hku.hken_HK
dc.identifier.emailSham, PC: pcsham@hku.hken_HK
dc.identifier.emailPoon, RT: poontp@hku.hken_HK
dc.identifier.emailLuk, JM: jmluk@hkucc.hku.hken_HK
dc.identifier.authorityLee, NP=rp00263en_HK
dc.identifier.authorityNg, IO=rp00335en_HK
dc.identifier.authoritySham, PC=rp00459en_HK
dc.identifier.authorityPoon, RT=rp00446en_HK
dc.identifier.authorityLuk, JM=rp00349en_HK
dc.description.naturepublished_or_final_versionen_US
dc.identifier.doi10.1186/1471-2407-11-481en_HK
dc.identifier.pmid22070665-
dc.identifier.pmcidPMC3240666-
dc.identifier.scopuseid_2-s2.0-80655128680en_HK
dc.identifier.hkuros197821-
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-80655128680&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume11en_HK
dc.identifier.isiWOS:000298170400001-
dc.publisher.placeUnited Kingdomen_HK
dc.identifier.scopusauthoridHao, K=34770116300en_HK
dc.identifier.scopusauthoridLamb, J=7201524642en_HK
dc.identifier.scopusauthoridZhang, C=9747304800en_HK
dc.identifier.scopusauthoridXie, T=35286182300en_HK
dc.identifier.scopusauthoridWang, K=35286098800en_HK
dc.identifier.scopusauthoridZhang, B=35427050800en_HK
dc.identifier.scopusauthoridChudin, E=6603175835en_HK
dc.identifier.scopusauthoridLee, NP=7402722690en_HK
dc.identifier.scopusauthoridMao, M=7102960472en_HK
dc.identifier.scopusauthoridZhong, H=35308330000en_HK
dc.identifier.scopusauthoridGreenawalt, D=12143427800en_HK
dc.identifier.scopusauthoridFerguson, MD=35208305500en_HK
dc.identifier.scopusauthoridNg, IO=7102753722en_HK
dc.identifier.scopusauthoridSham, PC=34573429300en_HK
dc.identifier.scopusauthoridPoon, RT=7103097223en_HK
dc.identifier.scopusauthoridMolony, C=23987362300en_HK
dc.identifier.scopusauthoridSchadt, EE=6701604029en_HK
dc.identifier.scopusauthoridDai, H=7402206916en_HK
dc.identifier.scopusauthoridLuk, JM=7006777791en_HK
dc.identifier.citeulike10021145-

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