Clinical Cancer Research CR Balducci Frontiers in Basic Cancer Research
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 Meeting Abstracts Online
Clinical Cancer Research 13, 7363, December 15, 2007. doi: 10.1158/1078-0432.CCR-07-0593
© 2007 American Association for Cancer Research
This Article
Right arrow Abstract Freely available
Right arrow Full Text (PDF)
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 Google Scholar
Google Scholar
Right arrow Articles by Pang, J.-Z.
Right arrow Articles by Tang, Z.-Y.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Pang, J.-Z.
Right arrow Articles by Tang, Z.-Y.

Imaging, Diagnosis, Prognosis

Loss of Heterozygosity at D8S298 Is a Predictor for Long-term Survival of Patients with Tumor-Node-Metastasis Stage I of Hepatocellular Carcinoma

Jin-Zhong Pang, Lun-Xiu Qin, Ning Ren, Zhen-Yu Hei, Qing-Hai Ye, Wei-Dong Jia, Bing-Sheng Sun, Guo-Ling Lin, Dao-Yong Liu, Yin-Kun Liu and Zhao-You Tang

Authors' Affiliation: Liver Cancer Institute and Zhongshan Hospital, Institutes of Biomedical Science, Fudan University, Shanghai, P.R. China

Requests for reprints: Zhao-You Tang, Liver Cancer Institute and Zhongshan Hospital, Fudan University, 136 Yi Xue Yuan Road, Shanghai 200032, P.R. China. Phone/Fax: 86-21-6403-7181; E-mail: zytang{at}scrap.stc.sh.cn.


   Abstract
Top
 Abstract
Materials and Methods
 Results
 Discussion
 References
 
Purpose: Our previous studies have shown that chromosome 8p deletion correlates with metastasis of hepatocellular carcinoma (HCC). This study was to determine whether 8p deletion could be used in predicting the prognosis of patients with HCC, particularly in those with early stage of HCC.

Experimental Design: A total of 131 patients with tumor-node-metastasis (TNM) stage I of HCC who underwent curative liver resection were enrolled. Loss of heterozygosity (LOH) was examined using 10 microsatellite markers at chromosome 8p, as well as 14 microsatellites at chromosome 1p, 17p, 4q, 13q, and 16q, and their association with 5-year overall survival (OS) and disease-free survival (DFS) of patients was analyzed.

Results: In the entire cohort of patients, the mean LOH frequency at these 24 loci was 43.2%; LOH frequencies at D8S298 and D1S199 were 31.5% and 33.7%, respectively. LOH at D8S298 was associated with a worse 5-year OS (P = 0.008) and DFS (P = 0.038) in patients with TNM stage I of HCC. Likewise, the patients with LOH at D1S199 had a worse 5-year OS (P < 0.001) and DFS (P = 0.014) compared with those without LOH at D1S199. In multivariate analyses, LOH at D8S298 was an independent predictor of decreased DFS (hazard ratio, 0.372; 95% 95% confidence interval, 0.146-0.948; P = 0.038), whereas LOH at D1S199 was an independent predictor of decreased OS (hazard ratio, 0.281; 95% confidence interval, 0.123-0.643; P = 0.003).

Conclusions: LOH at D8S298 and D1S199 is independently associated with a worse survival in patients with TNM stage I of HCC after curative resection and could serve as novel prognostic predictors for this subgroup of patients.

Hepatocellular carcinoma (HCC) is one of the most frequent human cancers worldwide, and it has been ranked the second leading cause of death from cancer in China since 1990s (1). Although during the past decades, much advances have been obtained in the clinical studies of HCC, including early detection, surgical resection, and liver transplantation, the general prognosis of population with HCC still remains dismal (2, 3). It is hard to predict the life expectancy of HCC patients. Many factors, such as patient's general conditions, macroscopic tumor morphology, and histopathologic features, as well as tumor staging system, have been proved of prognostic significance and could provide useful information in predicting the tumor recurrence and prognosis of patients and triaging the patients who need and may benefit from adjuvant therapy. However, these features cannot always provide exact enough information for the predictions of patients' outcome. Sometimes, the patients, although they have the same tumor-node-metastasis (TNM) stages of disease, histopathologic features of tumor, and treatment strategy (such as curative resection), have different clinical outcomes. Particularly, it is even harder to determine which individuals will have tumor relapse after surgical treatment in the patients with early stage (TNM stage I) of HCC who do not have significant vascular invasion, regional lymph node, or distant metastasis.

Identification of molecular characteristics of HCC could provide supplementary information that could be useful for dividing the patients with the same TNM stage of disease into different subgroups (molecular classification). This would facilitate the prediction of tumor recurrence and patients' outcome after operation and better selection of therapeutic strategies. A large number of molecular factors have been shown to have potential prognostic significance. However, to date, none of them has been proved to be specific enough, especially in predicting the prognosis and therapeutic outcomes of patients with TNM stage I of HCC.

It is well known that solid cancers arise as a consequence of the accumulation of genetic and epigenetic alterations within a single cell or group of cells. The stepwise accumulation of multiple genetic alterations can drive malignant tumors development and progression and also provide a range of nucleic acid–based molecular markers for neoplasia (4, 5). Loss of heterozygosity (LOH), as a tumor-derived genetic marker, can lead to genome instability and play a critical part in tumor progression, so it may account for some clinically aggressive phenotypes and provide prognostic information in the early stage of tumor.

Studies have shown that deletion of chromosome 8p occurs frequently in HCC (6–8). In our previous studies, we found that chromosome 8p deletion was associated with metastasis of HCC (9, 10), and one candidate metastatic suppressor gene HTPAP was cloned (11). Another group also showed that LOH at D8S298 (8p22) associated with intrahepatic metastasis of HCC (12). These imply that deletion of 8p may serve as a potential predictor of prognosis for patients with HCC. To evaluate the prognostic values of these genetic aberrations for patients with early stage of HCC, in this study, 10 microsatellite markers on chromosome 8p (13–15), as well as 14 microsatellites markers on 1p (16, 17), 17p (15, 18), 4q (19), 13q (20), and 16q (16, 21), all of which are known to contain candidate tumor suppressor genes or to function as prognostic factors, were selected to investigate LOH in tumor tissues from patients with TNM stage I of HCC and to determine whether the presence of LOH at certain loci is likely to be of prognostic value in early stage of HCC.


   Materials and Methods
Top
 Abstract
 Materials and Methods
Results
 Discussion
 References
 
Patient selection. A total of 131 patients with TNM stage I of HCC who underwent liver resection for HCC at Liver Cancer Institute, Fudan University from January 1999 to March 2000 were enrolled in this study. Of the 131 patients, 112 were men and 19 were women, whose ages ranged from 21 to 76 years (median, 51.8 years). One hundred and seventeen patients (89.3%) had the history of hepatitis B virus infection or were serum positive for HBsAg, and 113 patients (86.3%) had liver cirrhosis. Seventy-six patients (58.0%) had an elevated serum level of {alpha}-fetoprotein (AFP; >20 µg/L). All patients who had solitary tumors of primary HCC without vascular invasion, no regional lymph nodes metastasis, and no distant metastasis were classified as TNM stage I according to the 6th edition of International Union Against Cancer (22). They were further classified with Barcelona Clinic Liver Cancer (BCLC) staging classification and Cancer of the Liver Italian Program (CLIP) scoring systems for the prognostic analysis, which are considered more useful in predicting the prognosis of patients with HCC (23, 24). Of the tumors, 94 (71.8%) were larger than 3 cm and the remaining 37 (28.2%) were ≤3 cm in diameter; 85 tumors (64.9%) were well encapsulated. All surgical liver resections were curative, i.e., complete removal of the gross tumor with no residual tumor at the excision margin, serum AFP level dropped to normal level within 2 months after operation in patients with elevated AFP before surgery, and no residual tumor upon diagnostic imaging. None of the patients received preoperative chemotherapy or radiotherapy. The diagnosis of HCC was confirmed by two pathologists. All of the selected patients had also intact follow-up data of clinical outcome after operation.

This study was approved by the Ethics Committee of Zhongshan Hospital, Fudan University (20050310) and was in compliance with the Helsinki Declaration.

Tissue microdissection and DNA preparation. The tumor and nontumor tissues were obtained from formalin-fixed, paraffin-embedded archival material in the tissue bank of authors' institute. Consecutive sections were made from each paraffin block, and the first section was counterstained with H&E for histopathologic diagnosis and as a guide for microdissection. For each tumor sample, a tissue region, comprising at least 80% of tumor cells, was microdissected from 8-µm-thick unstained consecutive slides after deparaffinization using a surgical scalpel under stereomicroscopic guidance. Its corresponding nontumor tissue was also microdissected in the same way. Then genomic DNA was isolated from the microdissected tissues with the QIAamp DNA micro kit (Qiagen) according to the manufacturer's instruction. The DNA concentrations were estimated by spectrophotometry.

Microsatellite markers and PCR. A total of 24 microsatellite markers, including 10 markers from chromosome 8p and 14 from chromosome 1p, 17p, 4q, 13q, and 16q, were used for LOH analysis (Table 1 ). All of the primer sets were obtained from Genbank database, and the sense primers were labeled with 6-FAM or HEX. When possible, the markers were combined in multiplex fluorescence screening panels. PCR mixtures contained 20 to 50 ng of template DNA, 0.5 µL of 10 x PCR buffer, 0.6 µL of 25 mmol/L MgCl2, 0.1 µL of 10 mmol/L deoxynucleotide triphosphate mix, 0.2 pmol of each primer, and 0.2 unit of HotStar Taq DNA polymerase, with a final volume of 5 µL. The amplification reaction was done on a GeneAmp PCR System 9700 Thermal Cycler (ABI) according to the following procedures: 15 min of denaturation at 95°C, followed by a 14 touch-down cycles consisting of 30 s at 94°C, 60 s at 63°C (decrease 0.5°C each cycle), 90 s at 72°C, then 25 cycles of 30 s at 94°C, 60 s at 56°C, 90 s at 72°C, with a final extension of 10 min at 72°C.


View this table:
[in this window]
[in a new window]

  		Table 1. Microsatellite markers used for analysis of LOH

 
LOH analysis. PCR products of each clinical specimen were electrophoresed and analyzed with an ABI Prism 3730XL DNA Sequencer equipped with Genemapper version 3.0 software. Molecular weight marker GeneScan-500 ROX Size Standard (Applied Biosystems) was used in each lane. When two amplified bands per locus were detected in the corresponding DNA of nontumor liver tissues (as normal control DNA), the case was defined as informative for analysis. In informative patients, intensity calculations and comparisons of the specific alleles between normal control and tumor DNA were done to evaluate for LOH. LOH was scored according to the following formula: LOH index = (T1 / T2) / (N1 / N2), in which "T" was the tumor DNA sample, "N" was the normal DNA sample, and 1 and 2 were the intensities of smaller and larger alleles, respectively. For a specific locus, the cases showing homozygosity, microsatellite instability, and insufficient PCR amplification were scored as noninformative. Informative LOH could be defined if LOH index was <0.5 or >2.0. In case of doubtful LOH interpretation, the assays were repeated to verify and confirm the results. During the assessment of allelic status, investigators were blinded to the clinicopathologic characteristics and outcome of patients.

Statistical analysis. The statistical end points in our analysis were overall survival (OS) and disease-free survival (DFS). OS was defined as the interval from curative surgery to the date of death or the date of last contact if the patient was still alive, whereas DFS was defined as the interval from curative surgery to the date of documented tumor recurrence or the date of last contact with the patient if recurrence did not occur. Survival analysis was conducted with censoring of patients who died from other diseases or showed no evidence of recurrence. In a univariate analysis, survival curves were assessed by the Kaplan-Meier method, and differences between curves were analyzed using the log-rank test. OS and DFS rates were calculated as the rates ± SE. Factors that were significantly related to survival in univariate analysis were entered into the multivariate analysis.

Multivariate analysis was done with the use of a Cox proportional hazard model to identify variables that were independent predictors for clinical outcome. A forward stepwise selection with the likelihood ratio criterion (inclusion and exclusion criteria were P ≤ 0.05 and P ≥ 0.10, respectively) was used to identify the variables retained in the Cox model, with a P value of <0.05 considered to indicate statistical significance. The multivariate regression results were summarized using the estimated hazard ratio and 95% confidence interval for each variable entered into the Cox model. The SPSS version 11.5 software package was used for statistical analysis.


   Results
Top
 Abstract
 Materials and Methods
 Results
Discussion
 References
 
The relationship between clinicopathologic features and patient survival. Clinicopathologic characteristics of the patients enrolled in this study were detailed in Table 2 . The last follow-up was in March 2005. The median follow-up time was 60 months, ranging from 4 to 74 months. During the follow-up period, 54 patients died of cancer-related reasons and 54 patients were found with HCC recurrence.


View this table:
[in this window]
[in a new window]

  		Table 2. The associations of clinicopathologic characteristics with 5-y OS and DFS rates of patients with TNM stage I of HCC

 
A total of eight clinicopathologic variables, including patients' sex, age, serum AFP level, HBsAg, liver cirrhosis, tumor size, capsule, and differentiation (Edmondson's grade) were included in the univariate analysis to evaluate their associations with patients' survival. Besides, BCLC stage and CLIP score were also included. As shown in Table 2, liver cirrhosis (P = 0.030) and serum AFP level (P = 0.013) were associated with 5-year OS, whereas no variable was significantly associated with 5-year DFS of TNM stage I HCC patients. CLIP scores were significantly associated with both the 5-year OS (P = 0.001) and DFS (P = 0.001); however, no significant correlation was found between BCLC stages and the 5-year OS (P = 0.228) or DFS (P = 0.267) of patients with TNM stage I of HCC (Table 2).

LOH frequency at loci tested. The mean heterozygosity of the 24 loci tested was 69.9%. As shown in Table 1, the LOH frequencies assessed from informative cases at the 24 loci tested were also high, with a mean value of 43.2%, and the three most frequently altered loci were D17S831 (64.8%, 70 of 108) on 17p, D4S426 (60.7%, 54 of 89) on 4q, and D17S926 (56.7%, 59 of 104) on 17p. LOH at D8S298 on 8p (8p22) and D1S199 on 1p (1p36.1) were 31.5% and 33.7%, respectively (Table 1).

Correlation between LOH at loci tested and patients' outcomes. In the univariate analysis, LOH at D8S298 was found to significantly associate with a decreased probability of 5-year OS and DFS of patients with stage I of HCC. The 5-year OS and DFS rates of patients with LOH at D8S298 were much lower than that of patients without D8S298 LOH (46 ± 5% versus 62 ± 2% OS, P = 0.008 and 44 ± 5% versus 57 ± 3% DFS, P = 0.038; Table 3 ; Fig. 1A and B ). Likewise, LOH at D1S199 was strongly associated with both decreased 5-year OS and decreased DFS in the entire cohort of patients. Patients with LOH at D1S199 had a worse 5-year OS (42 ± 4% versus 61 ± 2%, P < 0.001) and DFS (41 ± 5% versus 57 ± 3%, P = 0.014) than those without D1S199 LOH (Table 3; Fig. 1C and D). However, no statistically significant correlation was observed between LOH at any other marker analyzed in this study and OS and DFS of patients, including those three most frequently altered loci D17S831, D17S926, and D4S426.


View this table:
[in this window]
[in a new window]

  		Table 3. The association of LOH on D8S298/D1S199 with the 5-y OS and DFS rates of patients with TNM stage I of HCC: a univariate analysis

 

Figure 1
View larger version (15K):
[in this window]
[in a new window]
[Download PPT slide]
  		Fig. 1. The association of LOH at D8S298 and D1S199 with the postoperative survival of patients with TNM stage I of HCC. Two-sided P values were calculated with the use of the log-rank test. A and B, 5-y OS (A) and DFS (B) rates of patients with LOH at D8S298 were much lower than that of patients without D8S298 LOH. C and D, likewise, patients with LOH at D1S199 had a worse 5-y OS (C) and DFS (D) than those without D1S199 LOH.

 
Variables, including the clinicopathologic characteristics and microsatellite markers that were found to have prognostic value in the univariate analysis, were added into the corresponding multivariate Cox model of survival. In the Cox model with OS, D1S199 LOH was independently associated with decreased OS, with hazard ratio of 0.281 (95% confidence interval, 0.123-0.643; P = 0.003), whereas liver cirrhosis, serum AFP level, CLIP score, and LOH at D8S298 did not have any independent value although they were associated with the OS of patients with HCC in univariate analysis (Table 4 ). And in the multivariate analysis of DFS (Table 4), D8S298 LOH was an independent predictor of decreased DFS, with hazard ratio of 0.372 (95% confidence interval, 0.146-0.948; P = 0.038); however, no significant prognostic value was found in LOH at D1S199 (P = 0.257) and CLIP score (P = 0.351).


View this table:
[in this window]
[in a new window]

  		Table 4. A multivariate Cox model analysis of factors related to 5-y OS and DSF of patients with TNM stage I of HCC

 

   Discussion
Top
 Abstract
 Materials and Methods
 Results
 Discussion
References
 
It is well known that the clinical stage is the most important factor influencing on the prognosis of HCC patients. Several systems are available for classification of HCC. The most common used is International Union Against Cancer's TNM staging system, and BCLC staging classification and CLIP scoring systems are considered more effective in predicting the prognosis of patients with HCC (23, 24). In general, these classification systems are based on the tumor morphology, number and size of tumor, status of vascular invasion, status of metastasis, serum AFP levels, and markers of hepatic reserve (25, 26). Although these systems have successfully graded the patients on their prognosis according to each variable, these systems still have the limitations for predicting the prognosis of patients with HCC, especially for those with early stage of disease and without vascular invasion. As shown in this study, BCLC staging classification system, which is based on tumor number, size, vascular invasion, and liver function, did no significant correlation with the OS or DFS of patients with TNM stage I of HCC. Moreover, although the CLIP score, which is based on liver function (Child-Pugh stage), tumor morphology, serum AFP level, and portal vein thrombosis, was one of the most important factors correlating to patients' survival in the univariate analysis, it did not show an independent prognostic value in the multivariate Cox model analysis. Among the clinicopathologic factors tested, except serum AFP level and liver cirrhosis related to OS of patients, no any significant prognostic value was found in the size, capsule status, and differentiation grade of tumor in patients with TNM stage I of HCC. Moreover, even AFP level and liver cirrhosis did not also have a significant value in multivariate Cox model analysis. So, using these systems, it is not possible to identify these patient subgroups and stratify individuals into prognostic groups within this given stage.

To overcome the limitations of these traditional classification systems, a large number of molecular markers (biomarkers) have been investigated and shown to have potential predictive significance (25). Recently, new technologies of molecular genetics and biology, such as analyses of genomic aberration, gene expression profiling, and proteomics, which provide new way to delineate new biomarkers genome-wide, have been applied to the HCC prediction and classification (27–29). In the previous works, we have generated two molecular signatures, one from the gene expression signatures of primary HCCs and another from the inflammation/immune response-related signature, which can classify the metastatic potentials of HCC and prognosis of patients with HCC (27, 30). But until now, none of them have been proved to be specific enough in predicting the prognosis and therapeutic outcomes of patients with HCC, particularly of those with early stage (TNM stage I) of HCC. Furthermore, their practical constraints are imposed by the cost of detection, difficulties in obtaining sufficient and well-annotated samples, the challenges in its reliability, and the interpretation of data obtained (30).

In recent years, it has been shown that identification and characterization of genetic alterations can provide a variety of molecular markers for certain cancers, which may ultimately offer new tools for early diagnosis, prediction of the effectiveness of treatment, and patients' prognosis. Among the genetic alterations, LOH may provide more accurate insight into tumor progression and predict clinical outcome (16, 31, 32). Compared with the RNA and protein profiling methods, LOH analysis is much stable and cost-efficient because it can be carried out by PCR with a small amount of DNA from the paraffin-embedded archival materials. These are very easily accessible for clinical patients.

It has been found that the deletion of 8p might serve as a novel prognostic indicator for various kinds of human cancers, such as colorectal cancer (13, 33), head and neck squamous cell carcinoma (34), and renal cell carcinoma (35). In our previous studies, chromosome 8p deletion was found to be closely associated with HCC metastasis (9, 10), and a candidate metastatic suppressor gene, HTPAP, was identified on chromosome 8p (11). These suggested that chromosome 8p deletion might contribute to HCC progression and metastasis, and detection of 8p deletion might be helpful in the prediction of HCC metastasis and clinical outcome of patients with HCC. In this study, we selected 10 microsatellite markers located at chromosome 8p and investigated the association of 8p deletion with the clinical outcome of patients with TNM stage I HCC after curative surgical treatment. Among the 10 microsatellite markers on chromosome 8p, LOH at D8S298, which is located at the region of 8p22, was found to be related to postoperative survival of patients with stage I of HCC, whereas no significant association with patients' survival was found for LOH at other loci. In the multivariate analysis, LOH at D8S298 was also an independent predictor for decreased DFS. These indicate that LOH at D8S298 can serve as a prognostic biomarker and facilitate the prediction of the tendency of postoperative recurrence of HCC patients at early stage. A previous study has also shown that LOH at D8S298 is associated with intrahepatic metastasis of HCC (12).

LOH on the region around chromosome 8p22 (at which the D8S298 is located) is a common event in several epithelial tumors including HCC (6–8, 13, 36). It has revealed 8p22 deletion to be the strongest variable to predict disease progression (37) and postoperative mortality (38). Thus far, several candidate tumor suppressor genes have been identified from 8p22, including DLC-1 (39), FEZ1/LZTS1 (40), N33, and EFA6R (41). Inactivation of DLC-1 may play an important role in development of liver and prostate cancers (42–44). DLC-1 can also act as a metastasis suppressor gene for breast cancer (45). The FEZ1/LZTS1 gene is inactivated in many cancers with 8p deletions, including prostate, esophageal, gastric, bladder, and breast cancer. Also, the FEZ1 protein has been shown to suppress growth of cancer cells and to regulate mitosis. A positive association between loss of FEZ1 expression and tumor grading and a tendency toward a reduction in the mortality rate in subjects with strong FEZ1 expression was found in lung cancer, which indicates an important role for FEZ1 in lung cancer, and suggests the possibility that it may serve as a novel prognostic indicator (46). Expression of N33 and EFA6R seems to also have an effect on OS in ovarian carcinoma (41). These indicate that the deletion of 8p22 may play an important role in the progression and could serve as a novel predictor for the surgical outcome of cancer patients, including those with early stage of HCC.

D1S199, located at 1p36, was another marker with prognostic value in this study. Like D8S298, LOH at D1S199 was significantly associated with decreased OS and DFS of patients with stage I HCC. Multivariate analysis showed LOH at D1S199 was an independent predictor for decreased OS but not for DFS. The exact reason of that is not clear. The prognostic value of deletion on 1p, including D1S199, have also been found in other kinds of malignancies, including Wilms' tumor (16), neuroblastoma (17), and colorectal cancer (47). Some studies also revealed that loss on 1p36 usually occurred in hepatocarcinogenesis (48, 49). Therefore, LOH on 1p36 could be another novel prognostic predictor for patients with early-stage HCC.

In addition, our results did not reveal any association between the allelic losses of microsatellite markers on chromosome 17p, 4q, 13q, and 16q and OS or DFS of patients with early-stage HCC, although LOH on 16q, 17p, and the numbers of chromosomes with LOH have been found to be significantly associated with metastasis-free survival of HCC and that LOH on 16q was the most useful prognostic indicator for metastasis after curative hepatic resection in a multivariate Cox survival analysis (50). Also, other studies exhibited that loss on 13q was linked to tumor recurrence and a more aggressive tumor behavior of HCC (20, 51). The true reason is not clear. A possible explanation for these varying reports regarding the prognostic significance of 13q, 16q, and 17p allelic deletion is that microsatellite markers selected from these chromosomes are different. Therefore, further prognostic studies of allelic losses on these chromosomes should be done.

In summary, we showed for the first time that LOH at D8S298 and D1S199 is associated with poor prognosis of patients with TNM stage I of HCC after curative liver resection in this study, which indicates that certain genetic alterations other than traditional prognostic factors can serve as prognostic markers in patients with early-stage HCC. These markers, in combination with the currently used prognostic factors, may allow for more precise prognosis prediction and treatment recommendations. For instance, even in patients with early-stage HCC without vascular invasion, those with LOH at D8S298 and D1S199 are at higher risk of recurrence after curative hepatic resection. Thus, they should be followed up intensively and recommended to give appropriate adjuvant therapy (such as immunobiotherapeutic strategies) after operation to delay or avoid recurrence. Obviously, combination of these novel prognostic biomarkers with currently used TNM stage would be of great value in predicting the prognosis of patients with HCC.


   Footnotes
 
Grant support: China National Natural Science Foundation for Distinguished Young Scholars 30325041, China National ‘863’ High-tech Project 2006AA02Z473, and Ministry of Education of China Foundation for Outstanding Scholars in New Era.

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: J-Z. Pang and L-X. Qin contributed equally to this work.

Received 3/12/07; revised 7/25/07; accepted 9/13/07.


   References
Top
 Abstract
 Materials and Methods
 Results
 Discussion
 References
 

  1. He J, Gu D, Wu X, et al. Major causes of death among men and women in China. N Engl J Med 2005;353:1124–34.[Abstract/Free Full Text]
  2. Portolani N, Coniglio A, Ghidoni S, et al. Early and late recurrence after liver resection for hepatocellular carcinoma: prognostic and therapeutic implications. Ann Surg 2006;243:229–35.[CrossRef][Medline]
  3. 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]
  4. Weihrauch M, Benicke M, Lehnert G, Wittekind C, Wrbitzky R, Tannapfel A. Frequent k-ras-2 mutations and p16(INK4A) methylation in hepatocellular carcinomas in workers exposed to vinyl chloride. Br J Cancer 2001;84:982–9.[CrossRef][Medline]
  5. Aoki T, Miyamoto A, Marubashi S, et al. Clinical value of alterations in p73 gene, related to p53 at 1p36, in human hepatocellular carcinoma. Int J Oncol 2004;24:441–6.[Medline]
  6. Li SP, Wang HY, Li JQ, et al. Genome-wide analyses on loss of heterozygosity in hepatocellular carcinoma in Southern China. J Hepatol 2001;34:840–9.[CrossRef][Medline]
  7. Nishimura T, Nishida N, Komeda T, Fukuda Y, Nakao K. Genotype stability and clonal evolution of hepatocellular carcinoma assessed by autopsy-based genome-wide microsatellite analysis. Cancer Genet Cytogenet 2005;161:164–9.[CrossRef][Medline]
  8. Moinzadeh P, Breuhahn K, Stutzer H, Schirmacher P. Chromosome alterations in human hepatocellular carcinomas correlate with etiology and histological grade-results of an explorative CGH meta-analysis. Br J Cancer 2005;92:935–41.[CrossRef][Medline]
  9. Qin LX, Tang ZY, Sham JS, et al. The association of chromosome 8p deletion and tumor metastasis in human hepatocellular carcinoma. Cancer Res 1999;59:5662–5.[Abstract/Free Full Text]
  10. Qin LX, Tang ZY, Ye SL, et al. Chromosome 8p deletion is associated with metastasis of human hepatocellular carcinoma when high and low metastatic models are compared. J Cancer Res Clin Oncol 2001;127:482–8.[CrossRef][Medline]
  11. Wu X, Jia HL, Wang YF, et al. HTPAP gene on chromosome 8p is a candidate metastasis suppressor for human hepatocellular carcinoma. Oncogene 2006;25:1832–40.[CrossRef][Medline]
  12. Chan KL, Lee JM, Guan XY, Fan ST, Ng IO. High-density allelotyping of chromosome 8p in hepatocellular carcinoma and clinicopathologic correlation. Cancer 2002;94:3179–85.[CrossRef][Medline]
  13. Halling KC, French AJ, McDonnell SK, et al. Microsatellite instability and 8p allelic imbalance in stage B2 and C colorectal cancers. J Natl Cancer Inst 1999;91:1295–303.[Abstract/Free Full Text]
  14. Liao C, Zhao M, Song H, Uchida K, Yokoyama KK, Li T. Identification of the gene for a novel liver-related putative tumor suppressor at a high-frequency loss of heterozygosity region of chromosome 8p23 in human hepatocellular carcinoma. Hepatology 2000;32:721–7.[CrossRef][Medline]
  15. Zhang LH, Qin LX, Ma ZC, et al. Allelic imbalance regions on chromosomes 8p, 17p, 19p related to metastasis of hepatocellular carcinoma: comparison between matched primary and metastatic lesions in 22 patients by genome-wide microsatellite analysis. J Cancer Res Clin Oncol 2003;129:279–86.[Medline]
  16. Grundy PE, Breslow NE, Li S, et al. Loss of heterozygosity for chromosomes 1p and 16q is an adverse prognostic factor in favorable-histology Wilms tumor: a report from the National Wilms Tumor Study Group. J Clin Oncol 2005;23:7312–21.[Abstract/Free Full Text]
  17. Attiyeh EF, London WB, Mosse YP, et al. Chromosome 1p and 11q deletions and outcome in neuroblastoma. N Engl J Med 2005;353:2243–53.[Abstract/Free Full Text]
  18. Guan XY, Sham JS, Tai LS, Fang Y, Li H, Liang Q. Evidence for another tumor suppressor gene at 17p13.3 distal to TP53 in hepatocellular carcinoma. Cancer Genet Cytogenet 2003;140:45–8.[CrossRef][Medline]
  19. Yeh SH, Lin MW, Lu SF, et al. Allelic loss of chromosome 4q21 approximately 23 associates with hepatitis B virus-related hepatocarcinogenesis and elevated {alpha}-fetoprotein. Hepatology 2004;40:847–54.[CrossRef][Medline]
  20. Wong CM, Lee JM, Lau TC, Fan ST, Ng IO. Clinicopathological significance of loss of heterozygosity on chromosome 13q in hepatocellular carcinoma. Clin Cancer Res 2002;8:2266–72.[Abstract/Free Full Text]
  21. Lin YW, Lee IN, Chen CH, et al. Deletion mapping of chromosome 16q24 in hepatocellular carcinoma in Taiwan and mutational analysis of the 17-β-HSD gene localized to the region. Int J Cancer 2001;93:74–9.[CrossRef][Medline]
  22. International Union Against Cancer (UICC). In: Sobin LH, Wittekind C, editors. TNM classification of malignant tumors [M]. 6th ed. New York: Wiley-Liss; 2002. p. 81–3.
  23. Llovet JM, Bru C, Bruix J. Prognosis of hepatocellular carcinoma: the BCLC staging classification. Semin Liver Dis 1999;19:329–38.[Medline]
  24. Kudo M, Chung H, Osaki Y. Prognostic staging system for hepatocellular carcinoma (CLIP score): its value and limitations, and a proposal for a new staging system, the Japan Integrated Staging Score (JIS score). J Gastroenterol 2003;38:207–15.[CrossRef][Medline]
  25. Qin LX, Tang ZY. Recent progress in predictive biomarkers for metastatic recurrence of human hepatocellular carcinoma: a review of the literature. J Cancer Res Clin Oncol 2004;130:497–513.[Medline]
  26. Sala M, Forner A, Varela M, Bruix J. Prognostic prediction in patients with hepatocellular carcinoma. Semin Liver Dis 2005;25:171–80.[CrossRef][Medline]
  27. Ye QH, Qin LX, Forgues M, et al. Predicting hepatitis B virus-positive metastatic hepatocellular carcinomas using gene expression profiling and supervised machine learning. Nat Med 2003;9:416–23.[CrossRef][Medline]
  28. Lee JS, Chu IS, Heo J, et al. Classification and prediction of survival in hepatocellular carcinoma by gene expression profiling. Hepatology 2004;40:667–76.[CrossRef][Medline]
  29. Ding SJ, Li Y, Tan YX, et al. From proteomic analysis to clinical significance: overexpression of cytokeratin 19 correlates with hepatocellular carcinoma metastasis. Mol Cell Proteomics 2004;3:73–81.[Abstract/Free Full Text]
  30. Budhu A, Forgues M, Ye QH, et al. Prediction of venous metastases, recurrence, and prognosis in hepatocellular carcinoma based on a unique immune response signature of the liver microenvironment. Cancer Cell 2006;10:99–111.[CrossRef][Medline]
  31. Tinker AV, Boussioutas A, Bowtell DDL. The challenges of gene expression microarrays for the study of human cancer. Cancer Cell 2006;9:333–9.[CrossRef][Medline]
  32. Marsit CJ, Hasegawa M, Hirao T, et al. Loss of heterozygosity of chromosome 3p21 is associated with mutant TP53 and better patient survival in non-small-cell lung cancer. Cancer Res 2004;64:8702–7.[Abstract/Free Full Text]
  33. Choi SW, Lee KJ, Bae YA, et al. Genetic classification of colorectal cancer based on chromosomal loss and microsatellite instability predicts survival. Clin Cancer Res 2002;8:2311–22.[Abstract/Free Full Text]
  34. Bockmuhl U, Ishwad CS, Ferrell RE, Gollin SM. Association of 8p23 deletion with poor survival in head and neck cancer. Otolaryngol Head Neck Surg 2001;124:451–5.[CrossRef][Medline]
  35. Presti JC, Jr., Wilhelm M, Reuter V, Russo P, Motzer R, Waldman F. Allelic loss on chromosomes 8 and 9 correlates with clinical outcome in locally advanced clear cell carcinoma of the kidney. J Urol 2002;167:1464–8.[CrossRef][Medline]
  36. Utada Y, Haga S, Kajiwara T, et al. Allelic loss at the 8p22 region as a prognostic factor in large and estrogen receptor negative breast carcinomas. Cancer 2000;88:1410–6.[Medline]
  37. Matsuyama H, Pan Y, Oba K, et al. Deletions on chromosome 8p22 may predict disease progression as well as pathological staging in prostate cancer. Clin Cancer Res 2001;7:3139–43.[Abstract/Free Full Text]
  38. Tsuneizumi M, Emi M, Hirano A, et al. Association of allelic loss at 8p22 with poor prognosis among breast cancer cases treated with high-dose adjuvant chemotherapy. Cancer Lett 2002;180:75–82.[CrossRef][Medline]
  39. Yuan BZ, Miller MJ, Keck CL, Zimonjic DB, Thorgeirsson SS, Popescu NC. Cloning, characterization, and chromosomal localization of a gene frequently deleted in human liver cancer (DLC-1) homologous to rat RhoGAP. Cancer Res 1998;58:2196–9.[Abstract/Free Full Text]
  40. Ishii H, Baffa R, Numata SI, et al. The FEZ1 gene at chromosome 8p22 encodes a leucine-zipper protein, and its expression is altered in multiple human tumors. Proc Natl Acad Sci U S A 1999;96:3928–33.[Abstract/Free Full Text]
  41. Pils D, Horak P, Gleiss A, et al. Five genes from chromosomal band 8p22 are significantly down-regulated in ovarian carcinoma: N33 and EFA6R have a potential impact on overall survival. Cancer 2005;104:2417–29.[CrossRef][Medline]
  42. Wong CM, Lee JM, Ching YP, Jin DY, Ng IO. Genetic and epigenetic alterations of DLC-1 gene in hepatocellular carcinoma. Cancer Res 2003;63:7646–51.[Abstract/Free Full Text]
  43. Zhou X, Thorgeirsson SS, Popescu NC. Restoration of DLC-1 gene expression induces apoptosis and inhibits both cell growth and tumorigenicity in human hepatocellular carcinoma cells. Oncogene 2004;23:1308–13.[CrossRef][Medline]
  44. Guan M, Zhou X, Soulitzis N, Spandidos DA, Popescu NC. Aberrant methylation and deacetylation of deleted in liver cancer-1 gene in prostate cancer: potential clinical applications. Clin Cancer Res 2006;12:1412–9.[Abstract/Free Full Text]
  45. Goodison S, Yuan J, Sloan D, et al. The RhoGAP protein DLC-1 functions as a metastasis suppressor in breast cancer cells. Cancer Res 2005;65:6042–53.[Abstract/Free Full Text]
  46. Nonaka D, Fabbri A, Roz L, et al. Reduced FEZ1/LZTS1 expression and outcome prediction in lung cancer. Cancer Res 2005;65:1207–12.[Abstract/Free Full Text]
  47. Kambara T, Sharp GB, Nagasaka T, et al. Allelic loss of a common microsatellite marker MYCL1: a useful prognostic factor of poor outcomes in colorectal cancer. Clin Cancer Res 2004;10:1758–63.[Abstract/Free Full Text]
  48. Koshikawa K, Nomoto S, Yamashita K, Ishigure K, Takeda S, Nakao A. Allelic imbalance at 1p36 in the pathogenesis of human hepatocellular carcinoma. Hepatogastroenterology 2004;51:186–91.[Medline]
  49. Kuroki T, Fujiwara Y, Tsuchiya E, et al. Accumulation of genetic changes during development and progression of hepatocellular carcinoma: loss of heterozygosity of chromosome arm 1p occurs at an early stage of hepatocarcinogenesis. Genes Chromosomes Cancer 1995;13:163–7.[Medline]
  50. Nishida N, Fukuda Y, Komeda T, et al. Prognostic impact of multiple allelic losses on metastatic recurrence in hepatocellular carcinoma after curative resection. Oncology 2002;62:141–8.[CrossRef][Medline]
  51. Kusano N, Okita K, Shirahashi H, et al. Chromosomal imbalances detected by comparative genomic hybridization are associated with outcome of patients with hepatocellular carcinoma. Cancer 2002;94:746–51.[CrossRef][Medline]




This Article
Right arrow Abstract Freely available
Right arrow Full Text (PDF)
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 Google Scholar
Google Scholar
Right arrow Articles by Pang, J.-Z.
Right arrow Articles by Tang, Z.-Y.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Pang, J.-Z.
Right arrow Articles by Tang, Z.-Y.

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 Meeting Abstracts Online