Clinical Cancer Research Molecular Diagnostics in Cancer Therapeutic Development: Fulfilling the Promise of Personalized Medicine Translational Cancer Medicine 2008: Cancer Clinical Trials and Personalized Medicine
HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
Cancer Research Clinical Cancer Research
Cancer Epidemiology Biomarkers & Prevention Molecular Cancer Therapeutics
Molecular Cancer Research Cancer Prevention Research
Cancer Prevention Journals Portal Cancer Reviews Online
Annual Meeting Education Book Cell Growth & Differentiation

This Article
Right arrow Abstract Freely available
Right arrow Full Text (PDF)
Right arrow Supplementary Data
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow reprints & permissions
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Cheung, S. T.
Right arrow Articles by So, S.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Cheung, S. T.
Right arrow Articles by So, S.
Clinical Cancer Research Vol. 11, 551-556, January 2005
© 2005 American Association for Cancer Research


Imaging, Diagnosis, Prognosis

Claudin-10 Expression Level is Associated with Recurrence of Primary Hepatocellular Carcinoma

Siu Tim Cheung1, Ka Ling Leung1, Ying Chi Ip1, Xin Chen4, Daniel Y. Fong3, Irene O. Ng2, Sheung Tat Fan1 and Samuel So5

Departments of 1 Surgery and Centre for the Study of Liver Disease, 2 Pathology, and 3 Clinical Trials Centre, University of Hong Kong, Pokfulam, Hong Kong, China; 4 Department of Biopharmaceutical Sciences, University of California San Francisco, San Francisco, California; and 5 Department of Surgery, Asian Liver Center, Stanford University School of Medicine, Stanford, California

Requests for reprints: Siu Tim Cheung, Department of Surgery, University of Hong Kong Medical Centre, L9-55, Faculty of Medicine Building, 21 Sassoon Road, Hong Kong, China. Phone: 852-2819-9651; Fax: 852-2818-4407; E-mail: stcheung{at}hkucc.hku.hk.


    ABSTRACT
 Top
 ABSTRACT
 INTRODUCTION
 PATIENTS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Purpose: Hepatocellular carcinoma (HCC) patients with the same clinicopathologic features can have remarkably different disease outcomes after curative hepatectomy. To address this issue, we evaluated the cDNA microarray gene expression profiles of HCCs and identified claudin-10 expression level was associated with disease recurrence. The aim of the current study is to validate the microarray data by an alternative research method applicable for routine practice.

Experimental Design: Quantitative reverse transcription–PCR (RT-PCR) was used to validate the microarray data on claudin-10 expression level. The assay was repeated on a separate HCC sample set to consolidate the prognostic significance of claudin-10.

Results: Claudin-10 expression level by quantitative RT-PCR and by microarray measurement showed a high concordance (r = 0.602, P < 0.001). Quantitative RT-PCR was repeated on a separate HCC sample set and the association of claudin-10 expression with recurrence was again confirmed (hazard ratio, 1.2; 95% confidence interval, 1.0-1.4; P = 0.011). By multivariable Cox regression analysis, claudin-10 expression and pathologic tumor-node-metastasis stage were independent factors for prediction of disease recurrence.

Conclusion: Claudin-10 expression of HCC can be used as a molecular marker for disease recurrence after curative hepatectomy.

Key Words: claudin-10 • gene expression • liver cancer • prognosis • recurrence


    INTRODUCTION
 Top
 ABSTRACT
 INTRODUCTION
 PATIENTS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Hepatocellular carcinoma (HCC) is a common lethal malignancy and is among the five leading causes of cancer death worldwide (1). The incidence is rising in the United States (2), United Kingdom (3), and Japan (4). In China, liver cancer is the second major cause of cancer death (5). Epidemiologic studies have shown that hepatitis B (HBV) and C virus (HCV) infections, alcohol-induced liver injury, and consumption of aflatoxin are closely associated with liver cancer. Extensive studies have been done to better understand the clinicopathologic features to improve the management of patients with HCC (6–11). However, conventional clinicopathologic parameters have limited predictive power, and patients with the same pathologic tumor-node-metastasis (pTNM) stage of disease can have very different disease outcomes (12, 13). Thus, we systematically analyzed the gene expression profiles of patients with HCC (14) to identify genes that the expression level associated with recurrence after curative hepatectomy. Claudin-10 was examined further to consolidate its clinical significance, as it ranks high in prognosis prediction and is a membrane-bound protein with potential therapeutic value. Because microarray facilities are not commonly available in routine laboratories, quantitative reverse transcription–PCR (RT-PCR) assay method is used as an alternative technique for transcript measurement. Furthermore, the prognostic prediction has to be validated in an independent data set to confirm that it works in general and not only in the group of patients from whom the data were derived (15).

In the current study, the claudin-10 expression level and its prognostic value as a novel molecular marker for HBV-related HCC was presented. The claudin-10 gene was annotated by the Ensembl automatic analysis pipeline (http://www.ensembl.org). The claudin-10 gene locates at chromosome 13q31-q34 spanning 25.51 kb with 5 exons, and the predicted protein contains four potential transmembrane domains. This gene encodes a member of the claudin family in which claudins are integral membrane proteins and components of tight junction strands (refer to ref. 16 for a review). The exact function of claudin-10 is unknown and its role in cancer development and progression is mysterious. Interestingly, the claudin family members have been shown to facilitate cell invasion and migration (16). In this report, the claudin-10 (NM_006984, encodes 228 amino acids) was characterized for its clinical significance as the predominant isoform observed in various tissue organs (National Center for Biotechnology Information GenBank) and in liver,6 and was reported to be overexpressed in lung cancer cell lines (17) and papillary thyroid carcinoma (18).


    PATIENTS AND METHODS
 Top
 ABSTRACT
 INTRODUCTION
 PATIENTS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Patients and Samples. We have recently reported the global gene expression profiles of HCC and the adjacent nontumor liver tissues examined by the cDNA microarray approach (14). In the present study, gene expression profiles from 48 patients undergoing curative partial hepatectomy for HCC during the period March 1999 to April 2000 at Queen Mary Hospital, Hong Kong, were included for patient outcome analysis. Patients were excluded from the present disease outcome analysis if the pathologic examination of the resected specimen showed positive resection margin or mixture of other tumor cell types (e.g., cholangiocarcinoma); if they had received chemotherapy before or after resection; if they had undergone liver transplantation instead of partial hepatectomy; if the resection was for recurrence or palliative intent; or if the resection was followed by hospital death. Another 53 HCCs operated on during the period April 2000 to March 2002 in the same institute with the same exclusion criteria were recruited for validation study. Informed consent had been obtained for specimen collection. The study protocol was approved by the Ethics Committee of the University of Hong Kong.

Diagnosis of HCC recurrence was based on typical imaging findings in a contrast-enhanced computed tomography scan and an increased serum {alpha}-fetoprotein (AFP) level. In case of uncertainty, hepatic arteriography and a post-Lipiodol computed tomography scan were done, and if necessary, fine-needle aspiration cytology was used for confirmation. Up to the date of analysis, 59 of the total 101 patients developed recurrence and the median disease-free period was 5.7 months (range, 0.9-32.7 months). For the remaining 42 patients who were disease free, the median follow-up period was 34.0 months (range, 14.9-48.8 months). The age of the patients ranged from 13 to 79, with a median age of 52 years. There were 81 men and 20 women. Serum hepatitis B surface antigen was positive in 92 patients (91.1%). Tumors were staged according to the Union International Contre Cancer pTNM tumor classification 1997 version (19), because the 2002 version did not clearly stratify the patients into different stages in terms of survival rate (20). The clinicopathologic features were prospectively collected into the HCC clinical database.

Microarray Expression Study. The cDNA microarray slides were printed with about 23,000 cDNA clones including 17,400 genes. Samples, RNA preparations, and hybridization protocols had been established and described in detail previously (14, 21). Data were deposited into the Stanford Microarray Database (http://genome-www5.stanford.edu/MicroArray/SMD/; ref. 22). A total of 1,404 cDNA clones with expression levels different by at least 4-fold from the mean in at least two samples were selected for further Cox regression analyses.

Quantitative RT-PCR. Quantitative RT-PCR was done as described (23). Human 18S rRNA primer and probe reagents (Predeveloped TaqMan Assay Reagents, Applied Biosystems, Foster City, CA) were used as the normalization control for subsequent multiplexed reactions. The relative amount of claudin-10, which had been normalized with control 18S for RNA amount variation and calibrator for plate-to-plate variation, was presented as the relative fold change in log 2 base. Transcript quantification was done in at least triplicates for every sample. Quantification was done using the ABI Prism 7700 sequence detection system (Applied Biosystems). Primers and probe for claudin-10 were CLDN10-F, 5'-CTGTG GAAGG CGTGC GTTA-3'; CLDN10-R, 5'-CAAAG AAGCC CAGGC TGACA-3'; and CLDN10-P, 5'-6FAM CCTCC ATGCT GGCGC MGBNFQ-3'.

Statistical Methods. Cox regression analyses with gene expression data as continuous variables were computed to examine gene expression that was associated with disease recurrence after curative resection. The technical concern of microarray data reproducibility was addressed by using quantitative RT-PCR for validation. Expression data by microarray and quantitative RT-PCR data were continuous variables assessed by Pearson's correlation coefficient (r). The association of claudin-10 expression and disease-free survival was validated in another independent sample set, and we used quantitative RT-PCR as a different assay technique for the transcript quantitation in the independent sample set.

The claudin-10 expression data were modeled as categorical variables only in the Kaplan-Meier analyses. The Youden index (sensitivity + specificity – 1; ref. 24) was used to determine the optimal cutoff point of claudin-10 expression for the prediction of 3-year disease-free survival. Other cutoff values including the mean, median, and 75th percentile had also been considered and examined, and they were all able to segregate the patients with clinical implications. The Youden index was used to maximize the sensitivity and specificity of the prediction simultaneously.

The association of gene expression and clinicopathologic parameters with patient outcome was examined by a multivariable Cox proportional hazards regression with the forward stepwise selection procedure. The claudin-10 expression data were modeled as continuous variable, and all the clinicopathologic parameters were modeled as categorical variables in the Cox regression analyses. The associations of claudin-10 expression level with clinicopathologic features were assessed by Spearman correlation and Mann-Whitney U test where appropriate. Differences were considered significant when P < 0.05. The statistical analyses were aided by SPSS version 11.0 software package (SPSS Inc., Chicago, IL).

Additional Microarray Information. The microarray study was carried out following the minimum information about microarray experiment guidelines issued by the Microarray Gene Expression Data Group (25). The original data are available in the Stanford Microarray Database (http://genome-www5.stanford.edu). Information is also available from the authors on request.


    RESULTS
 Top
 ABSTRACT
 INTRODUCTION
 PATIENTS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Claudin-10 Expression and Recurrence. Cox regression analyses with gene expression modeled as a continuous variable were computed to identify gene expression that predicts disease recurrence after curative resection (HCCs, n = 48; Supplementary Table 1). Claudin-10 ranks high in prognosis prediction and is a membrane-bound protein with potential therapeutic value. Claudin-10 encodes a member of the claudin family in which claudins are integral membrane proteins and components of tight junction strands. The claudin-10 level by cDNA microarray was significantly associated with recurrence [hazard ratio (HR), 1.7; 95% confidence interval (CI), 1.1-2.6; P = 0.014). To verify the technical concern on cDNA microarray reproducibility, quantitative RT-PCR was done on the same HCC sample set. Results derived from the two research methods showed a high concordance (Pearson correlation coefficient, r = 0.602, P < 0.001).

To provide an independent test of the association between claudin-10 expression and disease recurrence, a second set of primary HCCs was used (n = 53). Quantitative RT-PCR was used to measure the abundance of the claudin-10 transcript. The claudin-10 level was treated as a continuous variable, and Cox regression analysis was used to examine the relationship of the transcript level with disease recurrence of the patients after curative HCC surgery. Results indicated that the transcript level of claudin-10 was significantly associated with recurrence (HR, 1.2; 95% CI, 1.0-1.4; P = 0.011). Thus, the two sample sets examined by different techniques both indicated that a higher expression level of claudin-10 in HCC was associated with disease recurrence after curative surgery.

Prognosis by Claudin-10 Expression and Clinicopathologic Features. All the 101 patients in the two sample sets were included into the disease recurrence analyses. The claudin-10 expression data were based on quantitative RT-PCR, and were modeled as continuous variable in the analyses. For clinicopathologic parameters, patients were dichotomized accordingly (Table 1).


View this table:
[in this window]
[in a new window]
 
Table 1 Cox regression analyses for disease-free survival on gene expression and clinicopathologic parameters

 
By univariable Cox regression analysis, claudin-10 expression (HR, 1.2; 95% CI, 1.1-1.3; P = 0.002), late pTNM stages (HR, 3.0; 95% CI, 1.7-5.4, P < 0.001), venous invasion (HR, 2.6; 95% CI, 1.5-4.5, P < 0.001), large tumor size (HR, 2.2; 95% CI, 1.2-3.8; P = 0.006), multiple tumor nodules (HR, 1.9; 95% CI, 1.1-3.3; P = 0.025), and microsatellite nodules (HR, 1.7; 95% CI, 1.0-2.9; P = 0.037) were all significantly associated with disease recurrence. Gender, age, HBV association, serum AFP level, cirrhosis in the remnant liver, tumor encapsulation, and Edmondson-Steiner histologic grade were not significantly associated with recurrence.

By multivariable Cox regression analysis, claudin-10 expression (HR, 1.2; 95% CI, 1.1.1-1.3, P < 0.001), late pTNM stage (HR, 2.6; 95% CI, 1.4-4.7; P = 0.002), large tumor size (HR, 2.7; 95% CI, 1.5-4.9; P = 0.001), and high serum AFP level (HR, 2.2; 95% CI, 1.2-4.0; P = 0.010) were independent prognostic factors for disease recurrence. The other clinicopathologic features did not add independent prognostic information.

The Kaplan-Meier plot was used to further examine the prediction power by using the claudin-10 expression level alone or together with the pTNM stage system because these two factors were independent prognostic indicators by Cox regression analysis. By Youden index, the optimal cutoff value of claudin-10 expression was 1.23 (relative fold change in log 2 base) to segregate patients into low or high claudin-10 expression group. Using this cutoff value, there were 60 patients in the low claudin-10 expression group (range, 0-1.15) and 41 patients in the high claudin-10 expression group (range, 1.30-11.21). By using the claudin-10 factor alone to segregate the patients, the cumulative 3-year disease-free survivals for patients with low and high claudin-10 levels were 53.3% (32/60) and 24.4% (10/41), respectively (log-rank test, P < 0.001; Fig. 1). The analysis was repeated based on the claudin-10 level and pTNM stages of the patients. The cumulative 3-year disease-free survival was 75% (21/28) for early-stage (stages I and II) patients with low claudin-10 level, 40.0% (6/15) for early-stage patients with high claudin-10, 34.4% (11/32) for late-stage (stages III and IVa) patients with low claudin-10, and 15.4% (4/26) for late-stage patients with high claudin-10 (log-rank test, P < 0.001).



View larger version (16K):
[in this window]
[in a new window]
 
Fig. 1 Kaplan-Meier disease-free survival plot. A, all patients were categorized into low or high claudin-10 expression groups. B, early-stage (stages I and II) patients were further segregated according to claudin-10 expression level. C, late-stage (stages III and IVa) patients were further segregated according to claudin-10 expression level.

 
Decreased Claudin-10 Expression Was Associated with Older Patients, Presence of Tumor Capsule, and Noncirrhotic Liver. To better understand the significance of claudin-10 expression, we analyzed the association of claudin-10 expression level with the clinicopathologic parameters of the patients with HCC. The down-regulation of claudin-10 expression in tumor was significantly associated with older patients (r = –0.223, P = 0.025), presence of tumor capsule (P = 0.011), and noncirrhotic liver remnant (r = 0.257, P = 0.009). The claudin-10 expression level in tumor was not significantly associated with the pTNM stages, venous infiltration, tumor size, multiple tumor nodules, microsatellite nodules, gender, HBV association, serum AFP level, or Edmondson-Steiner histologic grade.


    DISCUSSION
 Top
 ABSTRACT
 INTRODUCTION
 PATIENTS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Stratifying patients with different risk of disease recurrence will become more important for patient benefit. In the present study, we validated the microarray data in another independent sample set and used quantitative RT-PCR for transcript quantitation in the independent sample set. Both data sets examined by different assay techniques showed that down-regulation of claudin-10 expression was associated with prolonged disease-free period after curative surgery. Our results indicated that prognosis for patients with HCC can be derived from the gene expression of primary tumors. The use of quantitative RT-PCR to assess the claudin-10 level is particularly feasible for the clinical setting, as the test is sensitive and the assay facilities are commonly available in routine laboratories for practical application. Cox regression multivariate analysis indicated that claudin-10 expression was independent of pTNM stage in predicting prognosis, and gene expression data used together with pTNM stage can have added power to provide more accurate prediction for disease outcome (Fig. 1).

This is the first report on claudin-10 expression associated with disease-free survival in patients with HCC after hepatectomy. We and others have reported the expression profiles of HCCs with the microarray approach (14, 21, 26–31), although there have been few reports on the association of gene expression with HCC patient outcomes. Notably, a recent report by Iizuka et al. showed a correlation of gene expression, a predictive system consisting of 12 genes, with early post-hepatectomy intrahepatic recurrence within 1 year (32). Claudin-10 did not reveal prognostic significance in the Iizuka et al. report, and the prognostic genes reported in the two cohorts of patients did not overlap. The discrepancy may be due to several reasons. First, in the study by Iizuka et al., the patients were mostly HCV related (22/33, 66.7%), whereas the majority of our patients were HBV related (92/101, 91.1%). Different HCC etiologies may actually involve different genes and thus recurrence-associated genes in HBV- and HCV-related HCC may be different. Second, the fundamental difference in clinical end point consideration (only intrahepatic recurrence within the first year after surgery in the report of Iizuka et al.; both intra- and/or extrahepatic recurrence within 3 years in our report) may account for the differences, because different genes may be responsible for early recurrence (within the first year) or late recurrence (after the first year). Furthermore, we considered both intra- and extrahepatic recurrence within 3 years as clinical end-point assessments because recurrence outside the liver was also important for disease management and the longer follow-up period would have included the majority of recurrence after curative surgery. It would thus be important to evaluate if claudin-10 expression level can predict 3-year disease recurrence in HCV-related HCCs.

The functional annotation of genes provides an insight into the underlying biological mechanism leading to cancer recurrence. The biological function of claudin-10 is unknown. Particularly, claudin family members have been shown to associate with cell invasion and migration (16). Overexpression of claudin-2 transforms a "tight" tight junction into a "leaky" tight junction in epithelial cells (33). Overexpression of claudin-11 induces proliferation and enhances migration in an oligodendrocyte cell line (34). Nonetheless, the role of claudins in human cancer is diverse. Overexpression of claudin-4/claudin-3 has been reported in pancreatic (35, 36), colorectal (37), and ovarian (38) cancer. Notably, claudin-4 expression decreases cell invasion and metastatic potential of pancreatic cancer (39). On the other hand, down-regulation of claudin-7/claudin-1 has been reported in head and neck squamous cell carcinomas (40) and breast cancer (41, 42). Claudin-10 has not been well characterized (16). Notably, claudin-10 is reported to be highly expressed in lung cancer cell lines (17) and papillary thyroid carcinoma (18). In HCC, low claudin-10 expression was associated with the more favorable features including older age of patients, presence of tumor capsule, and noncirrhotic liver remnant. More advanced stages of the HCCs were observed in young patients (9, 43). Absence of tumor capsule was an aggressive HCC feature and associated with early recurrence (7, 10). Operative mortality was higher in patients with cirrhotic liver, which was related to hepatic function reserve (11, 44). The biological role of the decreased claudin-10 level in contribution to favorable HCC prognosis is not clear. Preliminary immunohistochemistry analysis on the cell origin of claudin-10 indicated that in the HCCs with high level of claudin-10 transcript, strong membranous signal and granular cytoplasmic staining were observed in the neoplastic hepatocytes (Supplementary Fig. 1). Nonetheless, further investigation is required to define the role of the prognostic gene claudin-10 in carcinogenesis to delineate the exact molecular pathways leading to disease recurrence.

Our results indicate that claudin-10 expression can predict disease recurrence after curative surgery. We have commenced to examine the functional role of claudin-10 in the contribution to disease recurrence, targeting to provide a more complete picture on cancer progression for better disease management.


    ACKNOWLEDGMENTS
 
We thank the members of Hepatobiliary and Pancreatic Surgery at The University of Hong Kong and members of the Patrick Brown Laboratory in the Department of Biochemistry, Stanford Microarray Database, and Stanford Asian Liver Center at Stanford University for their support.


    FOOTNOTES
 
Grant support: Distinguished Research Achievement Award, Sun Chieh Yeh Research Foundation for Hepatobiliary and Pancreatic Surgery, and Seed Funding Program of the University of Hong Kong.

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

Note: Supplementary data for this are available at Clinical Cancer Research Online (http://clincancerres.aacrjournals.org).

6 S.T. Cheung and S.T. Fan, Unpublished data. Back

Received 6/30/04; revised 10/ 8/04; accepted 10/29/04.


    REFERENCES
 Top
 ABSTRACT
 INTRODUCTION
 PATIENTS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 

  1. Pisani P, Parkin DM, Bray F, Ferlay J. Estimates of the worldwide mortality from 25 cancers in 1990. Int J Cancer 1999;83:18–29.[Medline]
  2. El-Serag HB, Mason AC. Rising incidence of hepatocellular carcinoma in the United States. N Engl J Med 1999;340:745–50.[Abstract/Free Full Text]
  3. Taylor-Robinson SD, Foster GR, Arora S, Hargreaves S, Thomas HC. Increase in primary liver cancer in the UK, 1979-94. Lancet 1997;350:1142–3.[Medline]
  4. Okuda K, Fujimoto I, Hanai A, Urano Y. Changing incidence of hepatocellular carcinoma in Japan. Cancer Res 1987;47:4967–72.[Abstract/Free Full Text]
  5. Tang ZY. Hepatocellular carcinoma. J Gastroenterol Hepatol 2000;15 Suppl:G1–7.[CrossRef]
  6. Ng IO, Lai EC, Fan ST, Ng MM, So MK. Prognostic significance of pathologic features of hepatocellular carcinoma. A multivariate analysis of 278 patients. Cancer 1995;76:2443–8.[CrossRef][Medline]
  7. Poon RT, Fan ST, Ng IO, Lo CM, Liu CL, Wong J. Different risk factors and prognosis for early and late intrahepatic recurrence after resection of hepatocellular carcinoma. Cancer 2000;89:500–7.[CrossRef][Medline]
  8. Poon RT, Ng IO, Fan ST, et al. Clinicopathologic features of long-term survivors and disease-free survivors after resection of hepatocellular carcinoma: a study of a prospective cohort. J Clin Oncol 2001;19:3037–44.[Abstract/Free Full Text]
  9. Ng IO, Ng MM, Lai EC, Fan ST. Pathologic features and patient survival in hepatocellular carcinoma in relation to age. J Surg Oncol 1996;61:134–7.[Medline]
  10. Ng IO, Lai EC, Ng MM, Fan ST. Tumor encapsulation in hepatocellular carcinoma. A pathologic study of 189 cases. Cancer 1992;70:45–9.[CrossRef][Medline]
  11. Fan ST. Methods and related drawbacks in the estimation of surgical risks in cirrhotic patients undergoing hepatectomy. Hepatogastroenterology 2002;49:17–20.[Medline]
  12. Vauthey JN, Lauwers GY, Esnaola NF, et al. Simplified staging for hepatocellular carcinoma. J Clin Oncol 2002;20:1527–36.[Abstract/Free Full Text]
  13. Villa E, Colantoni A, Camma C, et al. Estrogen receptor classification for hepatocellular carcinoma: comparison with clinical staging systems. J Clin Oncol 2003;21:441–6.[Abstract/Free Full Text]
  14. Chen X, Cheung ST, So S, et al. Gene expression profiles in human liver cancers. Mol Biol Cell 2002;13:1929–39.[Abstract/Free Full Text]
  15. Simon R, Radmacher MD, Dobbin K, McShane LM. Pitfalls in the use of DNA microarray data for diagnostic and prognostic classification. J Natl Cancer Inst 2003;95:14–8.[Free Full Text]
  16. Gonzalez-Mariscal L, Betanzos A, Nava P, Jaramillo BE. Tight junction proteins. Prog Biophys Mol Biol 2003;81:1–44.[CrossRef][Medline]
  17. Sugita M, Geraci M, Gao B, et al. Combined use of oligonucleotide and tissue microarrays identifies cancer/testis antigens as biomarkers in lung carcinoma. Cancer Res 2002;62:3971–9.[Abstract/Free Full Text]
  18. Aldred MA, Huang Y, Liyanarachchi S, et al. Papillary and follicular thyroid carcinomas show distinctly different microarray expression profiles and can be distinguished by a minimum of five genes. J Clin Oncol 2004;22:3531–9.[Abstract/Free Full Text]
  19. Sobin LH, Whitekind C. TNM classification of malignant tumours. 5th ed. New York: John Wiley; 1997.
  20. Poon RT, Fan ST. Evaluation of the new AJCC/UICC staging system for hepatocellular carcinoma after hepatic resection in Chinese patients. Surg Oncol Clin N Am 2003;12:35–50.[Medline]
  21. Cheung ST, Chen X, Guan XY, et al. Identify metastasis-associated genes in hepatocellular carcinoma through clonality delineation for multi-nodular tumor. Cancer Res 2002;62:4711–21.[Abstract/Free Full Text]
  22. Sherlock G, Hernandez-Boussard T, Kasarskis A, et al. The Stanford Microarray Database. Nucleic Acids Res 2001;29:152–5.[Abstract/Free Full Text]
  23. Bustin SA. Absolute quantification of mRNA using real-time reverse transcription polymerase chain reaction assays. J Mol Endocrinol 2000;25:169–93.[Abstract]
  24. Youden WJ. Index for rating diagnostic tests. Cancer 1950;3:32–5.[CrossRef][Medline]
  25. Brazma A, Hingamp P, Quackenbush J, et al. Minimum information about a microarray experiment (MIAME)—toward standards for microarray data. Nat Genet 2001;29:365–71.[CrossRef][Medline]
  26. Kawai HF, Kaneko S, Honda M, Shirota Y, Kobayashi K. {alpha}-Fetoprotein-producing hepatoma cell lines share common expression profiles of genes in various categories demonstrated by cDNA microarray analysis. Hepatology 2001;33:676–91.[CrossRef][Medline]
  27. Lee J, Thorgeirsson SS. Functional and genomic implications of global gene expression profiles in cell lines from human hepatocellular cancer. Hepatology 2002;35:1134–43.[CrossRef][Medline]
  28. Neo SY, Leow CK, Vega VB, et al. Identification of discriminators of hepatoma by gene expression profiling using a minimal dataset approach. Hepatology 2004;39:944–53.[CrossRef][Medline]
  29. Okabe H, Satoh S, Kato T, et al. Genome-wide analysis of gene expression in human hepatocellular carcinomas using cDNA microarray: identification of genes involved in viral carcinogenesis and tumor progression. Cancer Res 2001;61:2129–37.[Abstract/Free Full Text]
  30. Shirota Y, Kaneko S, Honda M, Kawai HF, Kobayashi K. Identification of differentially expressed genes in hepatocellular carcinoma with cDNA microarrays. Hepatology 2001;33:832–40.[CrossRef][Medline]
  31. Xu XR, Huang J, Xu ZG, et al. Insight into hepatocellular carcinogenesis at transcriptome level by comparing gene expression profiles of hepatocellular carcinoma with those of corresponding noncancerous liver. Proc Natl Acad Sci U S A 2001;98:15089–94.[Abstract/Free Full Text]
  32. Iizuka N, Oka M, Yamada-Okabe H, et al. Oligonucleotide microarray for prediction of early intrahepatic recurrence of hepatocellular carcinoma after curative resection. Lancet 2003;361:923–9.[CrossRef][Medline]
  33. Amasheh S, Meiri N, Gitter AH, et al. Claudin-2 expression induces cation-selective channels in tight junctions of epithelial cells. J Cell Sci 2003;115:4969–76.[Abstract/Free Full Text]
  34. Tiwari-Woodruff SK, Buznikov AG, Vu TQ, et al. OSP/claudin-11 forms a complex with a novel member of the tetraspanin superfamily and ß1 integrin and regulates proliferation and migration of oligodendrocytes. J Cell Biol 2001;153:295–305.[Abstract/Free Full Text]
  35. Nichols LS, Ashfaq R, Iacobuzio-Donahue CA. Claudin 4 protein expression in primary and metastatic pancreatic cancer: support for use as a therapeutic target. Am J Clin Pathol 2004;121:226–30.[CrossRef][Medline]
  36. Michl P, Buchholz M, Rolke M, et al. Claudin-4: a new target for pancreatic cancer treatment using Clostridium perfringens enterotoxin. Gastroenterology 2001;121:678–84.[CrossRef][Medline]
  37. Miwa N, Furuse M, Tsukita S, Niikawa N, Nakamura Y, Furukawa Y. Involvement of claudin-1 in the ß-catenin/Tcf signaling pathway and its frequent upregulation in human colorectal cancers. Oncol Res 2000;12:469–76.[Medline]
  38. Rangel LB, Agarwal R, D'Souza T, et al. Tight junction proteins claudin-3 and claudin-4 are frequently overexpressed in ovarian cancer but not in ovarian cystadenomas. Clin Cancer Res 2003;9:2567–75.[Abstract/Free Full Text]
  39. Michl P, Barth C, Buchholz M, et al. Claudin-4 expression decreases invasiveness and metastatic potential of pancreatic cancer. Cancer Res 2003;63:6265–71.[Abstract/Free Full Text]
  40. Al Moustafa AE, Alaoui-Jamali MA, Batist G, et al. Identification of genes associated with head and neck carcinogenesis by cDNA microarray comparison between matched primary normal epithelial and squamous carcinoma cells. Oncogene 2002;21:2634–40.[CrossRef][Medline]
  41. Kominsky SL, Argani P, Korz D, et al. Loss of the tight junction protein claudin-7 correlates with histological grade in both ductal carcinoma in situ and invasive ductal carcinoma of the breast. Oncogene 2003;22:2021–33.[CrossRef][Medline]
  42. Kramer F, White K, Kubbies M, Swisshelm K, Weber BH. Genomic organization of claudin-1 and its assessment in hereditary and sporadic breast cancer. Hum Genet 2000;107:249–56.[CrossRef][Medline]
  43. Furuta T, Kanematsu T, Matsumata T, et al. Clinicopathologic features of hepatocellular carcinoma in young patients. Cancer 1990;66:2395–8.[CrossRef][Medline]
  44. Vauthey JN, Klimstra D, Franceschi D, et al. Factors affecting long-term outcome after hepatic resection for hepatocellular carcinoma. Am J Surg 1995;169:28–34.[CrossRef][Medline]



This article has been cited by other articles:


Home page
Molecular Cancer TherapeuticsHome page
Y. C. Ip, S. T. Cheung, Y. T. Lee, J. C. Ho, and S. T. Fan
Inhibition of hepatocellular carcinoma invasion by suppression of claudin-10 in HLE cells
Mol. Cancer Ther., November 1, 2007; 6(11): 2858 - 2867.
[Abstract] [Full Text] [PDF]


Home page
Am. J. Pathol.Home page
M. Lioni, P. Brafford, C. Andl, A. Rustgi, W. El-Deiry, M. Herlyn, and K. S.M. Smalley
Dysregulation of Claudin-7 Leads to Loss of E-Cadherin Expression and the Increased Invasion of Esophageal Squamous Cell Carcinoma Cells
Am. J. Pathol., February 1, 2007; 170(2): 709 - 721.
[Abstract] [Full Text] [PDF]


Home page
J. Pharmacol. Exp. Ther.Home page
C. Ebihara, M. Kondoh, N. Hasuike, M. Harada, H. Mizuguchi, Y. Horiguchi, M. Fujii, and Y. Watanabe
Preparation of a Claudin-Targeting Molecule Using a C-Terminal Fragment of Clostridium perfringens Enterotoxin
J. Pharmacol. Exp. Ther., January 1, 2006; 316(1): 255 - 260.
[Abstract] [Full Text] [PDF]


Home page
Cancer Res.Home page
P. J. Morin
Claudin Proteins in Human Cancer: Promising New Targets for Diagnosis and Therapy
Cancer Res., November 1, 2005; 65(21): 9603 - 9606.
[Abstract] [Full Text] [PDF]


This Article
Right arrow Abstract Freely available
Right arrow Full Text (PDF)
Right arrow Supplementary Data
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow reprints & permissions
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Cheung, S. T.
Right arrow Articles by So, S.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Cheung, S. T.
Right arrow Articles by So, S.


HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
Cancer Research Clinical Cancer Research
Cancer Epidemiology Biomarkers & Prevention Molecular Cancer Therapeutics
Molecular Cancer Research Cancer Prevention Research
Cancer Prevention Journals Portal Cancer Reviews Online
Annual Meeting Education Book Cell Growth & Differentiation