Clinical Cancer Research Meeting Calendar 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 14, 143, January 1, 2008. doi: 10.1158/1078-0432.CCR-07-1380
© 2008 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 HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Zlobec, I.
Right arrow Articles by Lugli, A.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Zlobec, I.
Right arrow Articles by Lugli, A.

Imaging, Diagnosis, Prognosis

Node-Negative Colorectal Cancer at High Risk of Distant Metastasis Identified by Combined Analysis of Lymph Node Status, Vascular Invasion, and Raf-1 Kinase Inhibitor Protein Expression

Inti Zlobec1, Kristi Baker2, Parham Minoo2, Jeremy R. Jass3, Luigi Terracciano1 and Alessandro Lugli1

Authors' Affiliations: 1 Institute of Pathology, University Hospital of Basel, Basel, Switzerland; 2 Department of Pathology, McGill University, Montreal, Quebec, Canada; and 3 Department of Cellular Pathology, St. Mark's Hospital, Middlesex, United Kingdom

Requests for reprints: Inti Zlobec, Institute of Pathology, University Hospital of Basel, Schönbeinstrasse 40, CH-4031 Basel, Switzerland. Phone: 410-61-265-28-95; Fax: 410-61-265-31-94; E-mail: izlobec{at}uhbs.ch.


   Abstract
Top
 Abstract
Materials and Methods
 Results
 Discussion
 References
 
Purpose: To identify independent clinicopathologic factors and protein markers leading to the identification of colorectal cancer (CRC) patients with mismatch repair proficiency at risk of developing metastasis and, consequently, more likely to benefit from combined modality therapy.

Experimental Design: Immunohistochemistry for 22 tumor markers was done using a tissue microarray. A subset of 387 CRC patients with complete clinicopathologic data and TNM stage was analyzed. Univariate and multivariate analyses were done to identify independent predictive markers of metastasis. The results were validated on 810 CRC patients.

Results: In univariate analysis, T stage (P < 0.001), N stage (P < 0.001), tumor grade (P = 0.005), vascular invasion (P < 0.001), tumor budding (P < 0.001), positive expression of β-catenin (P = 0.015), overexpression of RHAMM (P = 0.008), negative expression of Raf-1 kinase inhibitor protein (RKIP; P = 0.001), and absence of intraepithelial lymphocytes (P = 0.017) were significantly associated with the presence of distant metastasis. In multivariate analysis, higher N stage (P < 0.001), presence of vascular invasion (P = 0.009), and RKIP loss (P = 0.003) independently predicted distant metastatic disease. A subgroup of node-negative patients was identified as high risk for distant metastasis and showed a similar probability of metastatic risk and nearly identical survival times as node-positive patients with absence of vascular invasion and positive RKIP expression (metastatic risk, 24% and 22%; median survival time, 45.0 and 47.0 months, respectively).

Conclusion: The combined analysis of N stage, vascular invasion, and RKIP expression is highly predictive of distant metastasis in patients with mismatch repair–proficient CRC. Additionally, a subgroup of more aggressive N0 tumors can be identified by evaluating vascular invasion and RKIP expression.

The TNM classification remains the most reliable indicator of prognosis for patients with colorectal cancer (CRC) and provides the basis for therapeutic decision making (1). Patients with stage III disease and therefore with lymph node involvement are usually treated with adjuvant radiotherapy/chemotherapy whereas those without local metastatic spread typically undergo surgery (2). The treatment of patients with stage II disease by adjuvant chemotherapy remains a matter of controversy. The MOSAIC B2 meta-analysis of stage II subgroups showed a nonsignificant benefit in disease-free and overall survival with fluorouracil and leucovorin (3). On the other hand, the MOSAIC, QUASAR, and NSABP C-07 trials showed considerable improvements in survival in patients with node-negative disease (4–6). These results were supported by recent meta-analyses of fluorouracil-based adjuvant therapy for patients with stage II disease (7, 8).

Although high-risk node negative patients may benefit from adjuvant therapy, these patients are primarily identified as those with T4 lesions, perforation, poorly differentiated histology, and peritumoral lymphovascular involvement (9). Molecular characterization of tumors may improve the identification of patients at high risk of developing metastasis following surgery, thereby resulting in individualized treatment planning and improved selection of patients for adjuvant therapy (1).

Several tumor markers are currently being investigated for their prognostic or predictive value in CRC. Mutation of p53 is reported in ~70% of CRCs and is correlated with advanced disease stage, lymph node metastasis, and increased risk of distant metastasis in the majority of studies (10–17). The epidermal growth factor receptor has been linked to tumor progression, increased risk of liver metastasis, vascular invasion, and worse survival (18–22). Vascular endothelial growth factor has also been associated with liver metastasis and poorer survival time (23–25) and may confer a survival advantage to tumor cells by up-regulating the antiapoptotic protein Bcl-2 (26, 27). However, the prognostic value of this protein has not yet been fully established.

Apoptosis protease activating factor-1 (APAF-1) is a novel tumor marker recently investigated in CRC for its potential prognostic value. In mismatch repair–proficient tumors, loss of APAF-1 was significantly linked with more advanced T and N stage as well as poor survival (28). The metastatic potential of the Raf-1 kinase inhibitor protein (RKIP), a known critical down-regulator of the mitogen-activated protein kinase signaling pathway, has been shown in several tumor types (29–31). Loss of RKIP was also found to be associated with N stage, the presence of vascular invasion and metastasis in mismatch repair–proficient CRC, and worse survival time (28, 32).

The aim of this study was to identify clinicopathologic features, tumor markers, or combinations of these, leading to the identification of patients with mismatch repair–proficient CRC at high risk of developing metastasis and, consequently, more likely to benefit from adjuvant therapy. Using a tissue microarray, a comprehensive panel of 22 tumor markers and several well-established clinicopathologic features were analyzed on 387 CRC patients with known metastatic status. Independent predictive factors were identified and validated on a separate cohort of 810 patients with complete clinicopathologic data including 10-year follow-up. The protein markers selected for this study represent (a) novel and promising prognostic factors (APAF-1, RKIP, MST1, EphB2, CD44, MUC1, MUC2, tumor-infiltrating lymphocytes, and RHAMM); (b) known mediators of cell cycle arrest, proliferation, and apoptosis (Bcl-2, Ki-67, p21, p27, and p53); and (c) proteins involved in signaling pathways leading to tumor progression and metastasis, which include the Wnt (adenomatous polyposis coli, β-catenin, and E-cadherin), transforming growth factor-β (phosphor-SMAD2), Ras/mitogen-activated protein kinase, and phosphatidylinositol 3-kinase/AKT (phospho–extracellular signal–regulated kinase, epidermal growth factor receptor, and phospho-AKT) signaling pathways.


   Materials and Methods
Top
 Abstract
 Materials and Methods
Results
 Discussion
 References
 
Tissue microarray construction. A tissue microarray of 1,420 unselected, nonconsecutive primary CRCs was constructed (33). Briefly, formalin-fixed, paraffin-embedded tissue blocks of CRC resections were obtained. One tissue cylinder with a diameter of 0.6 mm was punched from morphologically representative tissue areas of each donor tissue block and brought into one recipient paraffin block (3 x 2.5 cm) using a home-made semiautomated tissue arrayer.

Immunohistochemistry. The 1,420 CRCs were dewaxed and rehydrated in distilled water. Following pressure cooker–mediated antigen retrieval in 0.001 mol/L EDTA (pH 8.0), endogenous peroxidase activity was blocked with 0.5% H2O2 and the sections were incubated with 10% normal goat serum (DakoCytomation) for 20 min. To determine mismatch repair status, the 1,420 CRCs were incubated with primary antibody for MLH1 (MLH1 clone MLH-1, BD Biosciences PharMingen), MSH2 (clone MSH-2, BD Biosciences PharMingen), and MSH6 (clone 44, Transduction Laboratories) at dilutions of 1/100 for 2 h at room temperature. Subsequently, sections were incubated with horseradish peroxidase–conjugated secondary antibody (DakoCytomation) for 30 min at room temperature. For visualization of the antigen, the sections were immersed in 3-amino-9-ethylcarbazole+substrate-chromogen (DakoCytomation) for 30 min and counterstained with Gill's hematoxylin. Immunohistochemistry was done similarly for a panel of 22 markers as outlined in Table 1 . In addition, CD8 was used as a marker for intraepithelial tumor-infiltrating lymphocytes.


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

  		Table 1. Characteristics of potential metastatic markers used for immunohistochemistry on 387 mismatch repair–proficient CRCs

 
Evaluation of immunohistochemistry. Immunoreactivity was assessed for each protein in a semiquantitative manner by scoring the proportion of positive tumor cells over the total number of tumor cells ranging from 0% to 100% using 5% increments (0%, 5%, 10%, etc.). The reproducibility of this scoring method between multiple pathologists has previously been assessed (22, 28, 34). Staining intensity was not assessed. MLH1, MSH2, and MSH6 were scored as negative (0% staining) or positive (>0% staining).

DNA mismatch repair status. The 1,420 CRCs were stratified according to DNA mismatch repair status and consisted of 1,197 mismatch repair–proficient tumors expressing MLH1, MSH2, and MSH6; 141 MLH1-negative tumors; and 82 presumed Lynch syndrome/hereditary nonpolyposis colorectal cancer cases showing loss of MSH2 and/or MSH6 at any age or loss of MLH1 at <55 years (35). Only mismatch repair–proficient cases were included in this study to ensure a homogeneous sample of CRCs.

Clinicopathologic data of mismatch repair–proficient CRCs. The clinicopathologic data for the 1,197 mismatch repair–proficient CRC patients included T stage, N stage, tumor grade, vascular invasion, and 10-year survival. Peritumoral lymphocyte invasion at the invasive front and tumor budding were evaluated using the original H&E slides of the resection specimens corresponding to each tissue microarray punch. The clinicopathologic features for patients with mismatch repair–proficient CRC are summarized in Table 2 .


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

  		Table 2. Clinicopathologic characteristics of patients with mismatch repair–proficient CRC (n = 1,197)

 
In addition to these features, M stage and treatment information was available for 387 CRCs. This subgroup of mismatch repair–proficient tumors was used as a test set to identify patients at high risk of metastasis. It included 74 (19.1%) patients with metastasis to the liver (stage IV disease; ref. 36), 54 (15.3%) with stage I tumors (T1 or T2, N0, M0), 112 (31.6%) with stage II (T3 or T4, N0, M0), and 119 (33.6%) with stage III (any T, >N0, M0). Most patients (n = 286) were treated with surgery alone whereas 88 also received adjuvant therapy.

Selecting cutoff scores for protein positivity/overexpression. A cutoff score for positive immunohistochemistry expression or overexpression for each of the 22 proteins was determined using receiver operating characteristic curve analysis (37). Briefly, the sensitivity and 1–specificity for discriminating presence and absence of metastasis was determined at each percentage score and plotted, thus generating a receiver operating characteristic curve. The (0, 1) criterion was used to select the score minimizing the trade-off between sensitivity and specificity, thus leading to the greatest number of tumors correctly classified as having metastasis or not. In addition, 100 bootstrapped replications were done to resample the data and determine the reliability of the cutoff scores for each protein.

Statistical analysis. The association of clinicopathologic features and protein expression with the presence of metastasis was evaluated using univariate logistic regression analysis on the first group of 387 mismatch repair–proficient CRC patients for whom M stage was known. P values, odds ratios (OR), and 95% confidence intervals (95% CI) were used to determine the effect of each variable on metastasis. All variables significantly associated (P < 0.05) with metastasis were entered into a multivariate logistic regression model. A forward selection procedure was used to identify independent predictors of metastasis. The probability of developing metastasis with each combination of predictors was obtained from the logistic regression equation (38). One hundred–fold cross-validation was done to determine the sensitivity and specificity of the final model. The combination of independent predictive factors was then validated on the remaining mismatch repair–proficient CRCs (n = 810) by survival analysis. The Kaplan-Meier method and the log-rank test were used in univariate survival analysis. The independent effect of each variable in multivariate analysis was determined by Cox proportional hazards regression and hazard ratios (HR) and 95% CIs were obtained. Due to the multiplicativity of HRs, the relative risk of death for each combination of features in the validation group was determined. The sensitivity and specificity of every combination for death from CRC were determined. All analyses were carried out using SAS version 9.1 (SAS Institute).


   Results
Top
 Abstract
 Materials and Methods
 Results
Discussion
 References
 
Association of clinicopathologic features with metastasis. T stage [P < 0.001; OR, 2.37 (1.57-3.57)], N stage [P < 0.001; OR, 7.28 (3.67-14.45)], tumor grade [P = 0.005; OR, 2.2 (1.25-3.87)], the presence of vascular invasion [P < 0.001; OR, 4.91 (2.85-8.46)], and tumor budding [P < 0.001; OR, 5.46 (2.96-10.1)], as well as the absence of peritumoral lymphocytes [P = 0.023; OR, 0.37 (0.16-0.91)], were significantly associated with the presence of metastasis. The median (95% CI) survival time for patients with metastatic disease was 14.0 (10.0-18.0) months (mean, 19.6 ± 2.5 months).

Association of protein expression with metastasis. Of the 22 tumor markers analyzed, only positive expression of nuclear β-catenin (P = 0.015), overexpression of cytoplasmic RHAMM (P = 0.008), negative expression of cytoplasmic RKIP (P = 0.001), and absence of intraepithelial lymphocytes (P = 0.017) were significantly associated with the presence of metastasis (Table 3 ).


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

  		Table 3. Association of tumor marker expression and presence of metastasis

 
Multivariate analysis of metastasis. Of the 10 clinicopathologic features and proteins entered into multivariate analysis, N stage [P < 0.001; OR, 9.43 (95% CI, 3.6-24.9)], vascular invasion [P = 0.009; OR, 2.83 (95% CI, 1.3-6.2)], and RKIP expression [P = 0.003; OR, 0.28 (95% CI, 0.12-0.65)] were found to independently predict metastasis (Table 4 ). Node-positive patients with vascular invasion and negative RKIP expression had the greatest probability of developing metastasis (probability = 0.75) whereas node-negative patients without vascular invasion and with positive RKIP expression had only a probability of 0.03. Interestingly, a subgroup of node-negative patients, which included T2 to T4 tumors, showed a nearly identical probability of metastatic risk (24%) with node-positive patients with no vascular invasion and positive RKIP expression (22%). The cross-validated sensitivity and specificity of the final model were 93% and 58%, respectively.


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

  		Table 4. Combinations of independent predictive factors and probability of developing metastasis

 
Survival analysis and validation of the final model. Validation of the predictive model was carried out on 810 mismatch repair–proficient CRCs by evaluating disease-specific survival time from patients with each combination of N stage, vascular invasion, and RKIP expression but whose M stage was not known. Immunohistochemical evaluation of RKIP was possible in 662 CRCs. Data on N stage and vascular invasion were available for all these patients. The same three variables again proved to be independently associated with survival: N stage [P < 0.001; HR, 2.46 (95% CI, 1.99-3.05)], vascular invasion [P < 0.001; HR, 1.98 (95% CI, 1.6-2.5)], and RKIP expression [P = 0.001; HR, 0.71 (95% CI, 0.6-0.8)]. The survival time for each combination of features as well as the sensitivity and specificity are listed in Table 5 . A comparison of the survival times with metastatic risk in Table 3 reveals several similarities between the two independent groups of patients. The longest survival time (107.0 months) corresponds to the combination N0/absence of invasion/positive RKIP, which was also found to have the lowest probability of metastatic risk and served as a baseline hazard (HR, 1.0). Patients with positive lymph nodes, presence of invasion, and negative RKIP were most likely to develop metastatic disease and also showed the worse survival (19.0 months). Moreover, their relative risk of death was determined to be 6.87 times greater than that for patients with N0 disease, with absence of vascular invasion and positive RKIP expression. All patients with these characteristics died of CRC within the first 58 months after diagnosis. Patients with the combination N0/presence of invasion and negative RKIP and patients with >N0/absence of invasion and positive RKIP not only had similar survival times (45.0 and 47.0 months, respectively) and relative risk of death (HR, 2.79 and 2.46, respectively) but were additionally found to have nearly identical probabilities of developing metastatic disease (0.24 and 0.22, respectively). Furthermore, patients with the most adverse combination of features and those with metastatic disease had comparable survival times (P = 0.997; Fig. 1 ).


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

  		Table 5. Survival time, sensitivity, and specificity for each combination of independent predictive factors

 

Figure 1
View larger version (12K):
[in this window]
[in a new window]
[Download PPT slide]
  		Fig. 1. Kaplan-Meier survival curve for patients with different combinations of N stage, vascular invasion, and RKIP expression (P < 0.0001). (1), N0, absence of invasion, positive RKIP (median, 107.0; 95% CI, 97.0-115.0 mo). (2), >N0, absence of invasion, positive RKIP (median, 47.0; 95% CI, 35.0-66.0 mo). (3), N0, presence of invasion, negative RKIP (median, 45.0; 95% CI, 30.0-67.0 mo). (4), >N0, presence of invasion, negative RKIP (median, 19.0; 95% CI, 12.0-29.0 mo).

 

   Discussion
Top
 Abstract
 Materials and Methods
 Results
 Discussion
References
 
Adjuvant chemotherapy/radiotherapy can improve prognosis in patients with resected CRC. Several studies have described overall 5-year survival rates approaching 20 months and response rates of nearly 50% with certain drug combinations (39). The most important prognostic factor and indicator of possible micrometastatic disease is tumor stage (TNM) at the time of surgery (1, 2). Although adjuvant therapy is considered standard care for patients with stage III disease, it is not routinely recommended for patients with stage II disease (2, 9). Unfortunately, 25% to 35% of these patients with pN0 cancers develop extranodular metastases within the first 5 years (40, 41).

The present study was undertaken to identify independent clinicopathologic factors and tumor markers leading to the identification of patients at risk of developing metastasis and, consequently, more likely to benefit from adjuvant therapy.

In multivariate analysis, the combination of N stage, vascular invasion, and RKIP expression provided independent predictive information on metastatic disease. In general, patients with lymph node involvement were more likely to develop metastasis than patients with N0 tumors regardless of vascular invasion and RKIP expression. Patients at highest risk of developing metastasis had lymph node involvement, vascular invasion, and negative immunohistochemical expression of RKIP, whereas the opposite features conferred a risk of only 3%. Interestingly, a subgroup of patients with N0 tumors showed a similar clinical outcome as node-positive disease. The sensitivity of the combined analysis of N stage, vascular invasion, and RKIP expression was high (93%), suggesting a strong predictive potential for this model.

To validate our findings, a second group of CRCs was included in the study. Patients were stratified according to N stage, vascular invasion, and RKIP expression. The 10-year disease-specific survival time was analyzed for each combination of features. Patients with the most adverse combination, and therefore with the highest risk of metastasis, also had the worst survival (19.0 months), whereas patients with the least amount of risk based on the predictive model (no lymph node involvement, absence of vascular invasion, and positive RKIP expression) showed a significantly longer survival time (107.0 months).

Not only was the risk of metastatic disease in patients with node-positive tumors with absence of invasion and positive RKIP expression (22%) nearly identical with that in patients with node-negative tumors with invasion and negative RKIP expression (24%) but also the survival times of both were strikingly similar (47.0 and 45.0, respectively).

The survival times of each combination of N stage, vascular invasion, and RKIP expression reflected metastatic risk in all but one occasion (i.e., in node-negative patients with vascular invasion and positive RKIP expression). The ORs and HRs for metastasis and survival time, respectively, show that RKIP expression has a significantly greater effect on predicting metastasis than vascular invasion whereas the opposite is found for survival time. The role of RKIP as a predictive marker of metastasis, rather than an independent prognostic factor, is highlighted by these results.

Several studies have identified the protein RKIP as a suppressor of metastasis (30–32, 42, 43). Loss of RKIP expression is associated with metastatic progression in breast cancer, prostate cancer, CRC, and melanoma, as well as with resistance to chemotherapy (30–32, 42–44). Our results have identified RKIP as the only independent predictive marker of metastasis among 21 other tumor markers studied by immunohistochemistry. The susceptibility of RKIP-negative tumors to chemotherapy has not yet been evaluated in CRC. The majority of the CRCs at higher metastatic risk in this study were indeed negative for the protein. Therefore, response of these patients to chemotherapy merits further investigation.

Several markers included in the analysis have previously been shown to have an effect on prognosis in patients with CRC, such as epidermal growth factor receptor. Sources contributing to discrepant findings from different prognostic studies include methodologic differences; poor study design; nonstandardized assays, which lack reproducibility; and inappropriate or misleading statistical analyses often done on underpowered patient samples (45). The recent REMARK recommendations for reporting of tumor markers in prognostic studies should help reduce these inconsistencies (45). In addition, a wide range of scoring methods used to evaluate immunoreactivity as well as the use of predetermined and often unvalidated or unjustified cutoff scores for tumor marker "positivity" is a major cause of the conflicting findings reported in the literature on the same tumor marker (46, 47).

In this study, we combined tissue microarray technology on >1,000 patients, a system made even more powerful by the use of a reproducible semiquantitative scoring method. Moreover, receiver operating characteristic curve analysis was used to select the most sensitive and specific cutoff scores for tumor marker positivity, with the presence or absence of metastasis as the end point, and validated by resampling of the data.

In conclusion, the combined analysis of N stage, vascular invasion, and RKIP expression is highly predictive of metastasis in patients with mismatch repair–proficient CRC. Additionally, these results suggest that a subgroup of more aggressive N0 tumors can be recognized by evaluating the presence of vascular invasion and expression of RKIP, thereby identifying stage II cancers that should be considered for radiotherapy or combined modality therapy.


   Acknowledgments
 
We thank Privatdozent Dr. Hanspeter Spichtin (Institute of Clinical Pathology Basel, Switzerland) and Professor Dr. Robert Maurer (Institute of Pathology, Stadtspital Triemli, Zurich, Switzerland) for providing the cases.


   Footnotes
 
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.

Received 6/ 4/07; revised 8/16/07; accepted 9/27/07.


   References
Top
 Abstract
 Materials and Methods
 Results
 Discussion
 References
 

  1. Weitz J, Koch M, Debus J, Hohler T, Galle PR, Buchler MW. Colorectal cancer. Lancet 2005;365:153–65.[CrossRef][Medline]
  2. Saltz LB, Minsky B. Adjuvant therapy of cancers of the colon and rectum. Surg Clin North Am 2002;82:1035–58.[CrossRef][Medline]
  3. International Multicentre Pooled Analysis of Colon Cancer Trials (IMPACT) investigators. Efficacy of adjuvant fluorouracil and folinic acid in colon cancer. Lancet 1995;345:939–44.[CrossRef][Medline]
  4. Andre T, Boni C, Mounedji-Boudiaf L, et al. Oxaliplatin, fluorouracil, and leucovorin as adjuvant treatment for colon cancer. N Engl J Med 2004;350:2343–51.[Abstract/Free Full Text]
  5. Wolmark N, Wieand HS, Kuebler JP, Colangelo L, Smith RE. A phase III trial comparing FULV to FULV + oxaliplatin in stage II or III carcinoma of the colon: results of NSABP Protocol C-07. Proc Am Soc Clin Oncol 2005;23:246s.
  6. Sobrero A. Should adjuvant chemotherapy become standard treatment for patients with stage II colon cancer? For the proposal. Lancet Oncol 2006;7:515–6.[CrossRef][Medline]
  7. Gill S, Loprinzi CL, Sargent DJ, et al. Pooled analysis of fluorouracil-based adjuvant therapy for stage II and III colon cancer: who benefits and by how much? J Clin Oncol 2004;22:1797–806.[Abstract/Free Full Text]
  8. Figueredo A, Charette ML, Maroun J, Brouwers MC, Zuraw L. Adjuvant therapy for stage II colon cancer: a systematic review from the Cancer Care Ontario Program in evidence-based care's gastrointestinal cancer disease site group. J Clin Oncol 2004;22:3395–407.[Abstract/Free Full Text]
  9. Benson AB III, Schrag D, Somerfield MR, et al. American Society of Clinical Oncology recommendations on adjuvant chemotherapy for stage II colon cancer. J Clin Oncol 2004;22:3408–19.[Abstract/Free Full Text]
  10. Garrity MM, Burgart LJ, Mahoney MR, et al. Prognostic value of proliferation, apoptosis, defective DNA mismatch repair, and p53 overexpression in patients with resected Dukes' B2 or C colon cancer: a North Central Cancer Treatment Group Study. J Clin Oncol 2004;22:1572–82.[Abstract/Free Full Text]
  11. Giatromanolaki A, Stathopoulos GP, Tsiobanou E, et al. Combined role of tumor angiogenesis, bcl-2, and p53 expression in the prognosis of patients with colorectal carcinoma. Cancer 1999;86:1421–30.[CrossRef][Medline]
  12. Haffty BG, Glazer PM. Molecular markers in clinical radiation oncology. Oncogene 2003;22:5915–25.[CrossRef][Medline]
  13. Mitomi H, Mori A, Kanazawa H, et al. Venous invasion and down-regulation of p21(WAF1/CIP1) are associated with metastasis in colorectal carcinomas. Hepatogastroenterology 2005;52:1421–6.[Medline]
  14. Munro AJ, Lain S, Lane DP. P53 abnormalities and outcomes in colorectal cancer: a systematic review. Br J Cancer 2005;92:434–44.[Medline]
  15. Russo A, Bazan V, Iacopetta B, Kerr D, Soussi T, Gebbia N. The TP53 colorectal cancer international collaborative study on the prognostic and predictive significance of p53 mutation: influence of tumor site, type of mutation, and adjuvant treatment. J Clin Oncol 2005;23:7518–28.[Abstract/Free Full Text]
  16. Schwandner O, Schiedeck TH, Bruch HP, Duchrow M, Windhoevel U, Broll R. p53 and Bcl-2 as significant predictors of recurrence and survival in rectal cancer. Eur J Cancer 2000;36:348–56.[CrossRef][Medline]
  17. Spitz FR, Giacco GG, Hess K, et al. p53 immunohistochemical staining predicts residual disease after chemoradiation in patients with high-risk rectal cancer. Clin Cancer Res 1997;3:1685–90.[Abstract]
  18. Gross ME, Zorbas MA, Danels YJ, et al. Cellular growth response to epidermal growth factor in colon carcinoma cells with an amplified epidermal growth factor receptor derived from a familial adenomatous polyposis patient. Cancer Res 1991;51:1452–9.[Abstract/Free Full Text]
  19. Prewett MC, Hooper AT, Bassi R, Ellis LM, Waksal HW, Hicklin DJ. Enhanced antitumor activity of anti-epidermal growth factor receptor monoclonal antibody IMC-C225 in combination with irinotecan (CPT-11) against human colorectal tumor xenografts. Clin Cancer Res 2002;8:994–1003.[Abstract/Free Full Text]
  20. Radinsky R. Modulation of tumor cell gene expression and phenotype by the organ-specific metastatic environment. Cancer Metastasis Rev 1995;14:323–38.[CrossRef][Medline]
  21. Radinsky R, Risin S, Fan D, et al. Level and function of epidermal growth factor receptor predict the metastatic potential of human colon carcinoma cells. Clin Cancer Res 1995;1:19–31.[Abstract/Free Full Text]
  22. Zlobec I, Vuong T, Hayashi S, et al. A simple and reproducible scoring system for EGFR in colorectal cancer: application to prognosis and prediction of response to preoperative brachytherapy. Br J Cancer 2007;96:793–800.[CrossRef][Medline]
  23. Des Guetz G, Uzzan B, Nicolas P, et al. Microvessel density and VEGF expression are prognostic factors in colorectal cancer. Meta-analysis of the literature. Br J Cancer 2006;94:1823–32.[CrossRef][Medline]
  24. Horkko TT, Klintrup K, Makinen JM, et al. Budding invasive margin and prognosis in colorectal cancer—no direct association with β-catenin expression. Eur J Cancer 2006;42:964–71.[CrossRef][Medline]
  25. Takahashi Y, Bucana CD, Cleary KR, Ellis LM. p53, vessel count, and vascular endothelial growth factor expression in human colon cancer. Int J Cancer 1998;79:34–8.[CrossRef][Medline]
  26. Gerber HP, McMurtrey A, Kowalski J, et al. Vascular endothelial growth factor regulates endothelial cell survival through the phosphatidylinositol 3'-kinase/Akt signal transduction pathway. Requirement for Flk-1/KDR activation. J Biol Chem 1998;273:30336–43.[Abstract/Free Full Text]
  27. Pidgeon GP, Barr MP, Harmey JH, Foley DA, Bouchier-Hayes DJ. Vascular endothelial growth factor (VEGF) up-regulates BCL-2 and inhibits apoptosis in human and murine mammary adenocarcinoma cells. Br J Cancer 2001;85:273–8.[CrossRef][Medline]
  28. Zlobec I, Minoo P, Baker K, et al. Loss of APAF-1 expression is associated with tumour progression and adverse prognosis in colorectal cancer. Eur J Cancer 2007;43:1101–7.[CrossRef][Medline]
  29. Fu Z, Kitagawa Y, Shen R, et al. Metastasis suppressor gene Raf kinase inhibitor protein (RKIP) is a novel prognostic marker in prostate cancer. Prostate 2006;66:248–56.[CrossRef][Medline]
  30. Hagan S, Al-Mulla F, Mallon E, et al. Reduction of Raf-1 kinase inhibitor protein expression correlates with breast cancer metastasis. Clin Cancer Res 2005;11:7392–7.[Abstract/Free Full Text]
  31. Schuierer MM, Bataille F, Hagan S, Kolch W, Bosserhoff AK. Reduction in Raf kinase inhibitor protein expression is associated with increased Ras-extracellular signal-regulated kinase signaling in melanoma cell lines. Cancer Res 2004;64:5186–92.[Abstract/Free Full Text]
  32. Al-Mulla F, Hagan S, Behbehani AI, et al. Raf kinase inhibitor protein expression in a survival analysis of colorectal cancer patients. J Clin Oncol 2006;24:5672–9.[Abstract/Free Full Text]
  33. Sauter G, Simon R, Hillan K. Tissue microarrays in drug discovery. Nat Rev Drug Discov 2003;2:962–72.[CrossRef][Medline]
  34. Zlobec I, Steele R, Michel RP, Compton CC, Lugli A, Jass JR. Scoring of p53, VEGF, Bcl-2 and APAF-1 immunohistochemistry and interobserver reliability in colorectal cancer. Mod Pathol 2006;19:1236–42.[CrossRef][Medline]
  35. Hampel H, Stephens JA, Pukkala E, et al. Cancer risk in hereditary nonpolyposis colorectal cancer syndrome: later age of onset. Gastroenterology 2005;129:415–21.[CrossRef][Medline]
  36. American Joint Committee on Cancer (AJCC) cancer staging manual. 6th ed. In: Greene FL, Page DL, Fleming ID, Fritz AG, Balch ChM, Haller DG, Morrow M, editors. New York (NY): Springer; 2002.
  37. Zlobec I, Steele R, Terracciano L, Jass J, Lugli A. Selecting immunohistochemical cutoff scores for novel biomarkers of progression and survival in colorectal cancer. J Clin Pathol 2007;60:1112–6.[Abstract/Free Full Text]
  38. Hosmer D, Lemeshow S. Applied logistic regression. New York: Wiley & Sons; 1989. p. 1–23.
  39. Saletti P, Cavalli F. Metastatic colorectal cancer. Cancer Treat Rev 2006;32:557–71.[CrossRef][Medline]
  40. Eisenberg B, Decosse JJ, Harford F, Michalek J. Carcinoma of the colon and rectum: the natural history reviewed in 1704 patients. Cancer 1982;49:1131–4.[CrossRef][Medline]
  41. Millikan KW, Staren ED, Doolas A. Invasive therapy of metastatic colorectal cancer to the liver. Surg Clin North Am 1997;77:27–48.[CrossRef][Medline]
  42. Chatterjee D, Bai Y, Wang Z, et al. RKIP sensitizes prostate and breast cancer cells to drug-induced apoptosis. J Biol Chem 2004;279:17515–23.[Abstract/Free Full Text]
  43. Fu Z, Smith PC, Zhang L, et al. Effects of raf kinase inhibitor protein expression on suppression of prostate cancer metastasis. J Natl Cancer Inst 2003;95:878–89.[Abstract/Free Full Text]
  44. Minoo P, Zlobec I, Baker K, et al. Loss of Raf-1 kinase inhibitor protein (RKIP) expression is associated with tumor progression and metastasis in colorectal cancer. Am J Clin Pathol 2007;127:820–7.[Abstract/Free Full Text]
  45. McShane LM, Altman DG, Sauerbrei W, Taube SE, Gion M, Clark GM. Reporting recommendations for tumor marker prognostic studies (REMARK). J Natl Cancer Inst 2005;97:1180–4.[Abstract/Free Full Text]
  46. Mamounas E, Wieand S, Wolmark N, et al. Comparative efficacy of adjuvant chemotherapy in patients with Dukes' B versus Dukes' C colon cancer: results from four National Surgical Adjuvant Breast and Bowel Project adjuvant studies (C-01, C-02, C-03, and C-04). J Clin Oncol 1999;17:1349–55.[Abstract/Free Full Text]
  47. Zlobec I, Terracciano L, Jass JR, Lugli A. Value of staining intensity in the interpretation of immunohistochemistry for tumor markers in colorectal cancer. Virchows Arch 2007;451:763–9.[CrossRef][Medline]



This article has been cited by other articles:


Home page
 Postgrad. Med. J.Home page
I Zlobec and A Lugli
Prognostic and predictive factors in colorectal cancer
Postgrad. Med. J., August 1, 2008; 84(994): 403 - 411.
[Abstract] [Full Text] [PDF]

Home page
 J. Clin. Pathol.Home page
I Zlobec and A Lugli
Prognostic and predictive factors in colorectal cancer
J. Clin. Pathol., May 1, 2008; 61(5): 561 - 569.
[Abstract] [Full Text] [PDF]

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 HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Zlobec, I.
Right arrow Articles by Lugli, A.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Zlobec, I.
Right arrow Articles by Lugli, A.

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