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Journal of Clinical Oncology, Vol 25, No 19 (July 1), 2007: pp. 2735-2740 © 2007 American Society of Clinical Oncology. DOI: 10.1200/JCO.2006.08.2867 Cell Cycle Regulators and Outcome of Adjuvant Cisplatin-Based Chemotherapy in Completely Resected Non–Small-Cell Lung Cancer: The International Adjuvant Lung Cancer Trial Biologic Program
From the Departments of Medicine I and Clinical Pathology, Medical University of Vienna, Vienna; Institute of Pathology, Medical University of Graz, Graz, Austria; Biostatistics and Epidemiology Unit, Department of Medicine, Institut Gustave Roussy, Villejuif; L'Institut National de la Santé et de la Recherche Médicale U823, Université Joseph Fourier, Department of Pathology, Grenoble Hospital, Grenoble, France; and Department of Internal Medicine, University Hospital of Zurich, Zurich, Switzerland Address reprint requests to Martin Filipits, PhD, Institute of Cancer Research, Department of Medicine I, Medical University of Vienna, Borschkegasse 8a, A-1090 Vienna, Austria; e-mail: martin.filipits{at}meduniwien.ac.at
Purpose: The International Adjuvant Lung Cancer Trial (IALT) demonstrated that adjuvant cisplatin-based chemotherapy improves the survival of patients with completely resected non–small-cell lung cancer (NSCLC). The purpose of our study was to determine whether cell cycle regulators are of prognostic and/or predictive value in patients who were enrolled onto the IALT. Patients and Methods: Expression of p27Kip1, p16INK4A, cyclin D1, cyclin D3, cyclin E, and Ki-67 was immunohistochemically assessed in tumor specimens obtained from 778 IALT patients. Prognostic and predictive analyses were based on Cox models adjusted for clinical and pathologic parameters. Results: There was a relationship between p27Kip1 status and benefit of cisplatin-based chemotherapy (test for interaction, P = .02). Among patients with p27Kip1-negative tumors, cisplatin-based chemotherapy resulted in longer overall survival compared with controls (adjusted hazard ratio [HR] for death = 0.66; 95% CI, 0.50 to 0.88; P = .006). In patients with p27Kip1-positive tumors, overall survival was not different between patients treated with cisplatin-based chemotherapy and controls (adjusted HR for death = 1.09; 95% CI, 0.82 to 1.45; P = .54). The other cell cycle regulators and Ki-67 did not predict benefit of adjuvant cisplatin-based chemotherapy. None of these biomarkers was significantly associated with overall survival of the patients in the total study population. Conclusion: NSCLC patients with p27Kip1-negative tumors benefit from adjuvant cisplatin-based chemotherapy after complete tumor resection. Before establishing p27Kip1 as a routine marker for selection of patients for adjuvant chemotherapy, the predictive value of p27Kip1 has to be confirmed in patients from other trials.
Approximately one third of non–small-cell lung cancer (NSCLC) patients present with early-stage disease and undergo surgery with curative intent. Despite complete tumor resection, however, distant metastases develop in 50% to 70% of these patients and lead to 5-year survival rates of approximately 40%.1 Adjuvant chemotherapy has recently been re-evaluated in clinical trials on large patient populations.2-7 The International Adjuvant Lung Cancer Trial (IALT), the largest of these trials, demonstrated that adjuvant cisplatin-based chemotherapy improves the 5-year survival rate of patients with completely resected NSCLC by an absolute value of 4.1%.3 Two further randomized studies have confirmed the benefit of adjuvant cisplatin-based chemotherapy in stage IB to IIIA NSCLC,5,6 whereas the Cancer and Leukemia Group B 9633 trial did not demonstrate a significant survival benefit in patients with stage IB disease.7 A pooled analysis of the five largest trials, the Lung Adjuvant Cisplatin Evaluation, indicates that adjuvant cisplatin-based chemotherapy improves survival at 5 years by an absolute value of 5%.8 Thus, adjuvant chemotherapy can now be considered as standard treatment for selected patients with completely resected NSCLC, particularly patients with stage II and III disease. The benefit from adjuvant chemotherapy is limited to a subgroup of patients. Clinical parameters, including sex, histologic type, and tumor stage, do not allow for the selection of these patients.3,8 Thus, biomarkers have become of interest as potential predictors for outcome of adjuvant chemotherapy. Of particular interest are biomarkers that are involved in cell cycle regulation. Cyclins, their associated cyclin-dependent kinases, and cyclin-dependent kinase inhibitory proteins play a central role in cell cycle progression and may also affect response to chemotherapy.9,10 The purpose of our study was to determine whether the cell cycle regulators p27Kip1, p16INK4A, cyclin D1, cyclin D3, and cyclin E and the proliferation marker Ki-67 are of prognostic and/or predictive value in NSCLC patients who were enrolled onto the IALT.
Patients and Study Design The present research is part of the IALT Biologic Program. We retrospectively collected paraffin-embedded tumor blocks from IALT centers that enrolled more than 10 patients onto IALT. Twenty-eight centers in 14 countries contributed samples (see Appendix, online only). Approval was obtained by local institutional review boards according to the legal regulations in each participating country. All tumor specimens were obtained at the time of surgery. The 28 centers enrolled 1,045 patients onto IALT, and we succeeded in collecting tumor blocks from 867 patients. The amount and quality of 824 of the 867 blocks were adequate for serial sectioning. Among these 824 blocks, 783 contained tumor material corresponding to NSCLC and were used for further analyses.
Immunohistochemistry Both external and internal positive controls were used. External positive controls were NSCLC samples known to express the given antigen. Internal positive controls included lymphocytes, endothelial cells, and fibroblasts (Appendix Table A1). Immunostaining was examined by experienced lung pathologists (K.S.: p27Kip1, cyclin D3, and Ki-67; S. L. and E. B.: p16INK4A, cyclin D1, and cyclin E) who were blinded to the clinical outcome of the patients. Immunostaining was classified based on staining intensity and percentage of stained cells. For all markers, only nuclear staining was scored as positive. Staining intensity was determined as 0 (absent), 1 (weak), 2 (moderate), or 3 (strong). For comparison with clinical parameters and survival, expression levels of the biomarkers were semiquantified using an immunohistochemistry score (range, 0 to 300) calculated by multiplying staining intensity with the percentage of positive tumor cells. The median value of this score was a priori chosen as a cutoff point to classify marker-positive and marker-negative tumors.
Statistical Analysis
To study selection bias within the IALT Biologic Program participating centers, the pre–random assignment characteristics of patients for whom tumor blocks were available and of patients without blocks were compared using Survival rates were estimated using the Kaplan-Meier method. The prognostic values of the biomarker status and chemotherapy for survival were studied using the Cox model to incorporate factors related to survival and/or the biomarker. As in the IALT analysis, the Cox model included every factor used in the stratified random assignment (center, tumor stage, and type of surgery) plus clinical and histologic prognostic factors (age, sex, WHO performance status, nodal status, lymphoid infiltration, and the revised histopathologic type). All other factors that were statistically related to the biomarker status in the multivariate logistic model (P < .05) were added to the survival Cox model to be sure that the prognostic role of a marker could not be explained by a simple clinical or histologic variable. The predictive value of the biomarkers was studied by testing the interaction between the biomarker status and the attributed treatment (chemotherapy or no chemotherapy) in the same Cox model. Sensitivity analyses using Cox models with a lower number of adjustment factors were performed, and the results were similar. Therefore, only results corresponding to the above model are presented. All reported P values were two sided. In the statistical analysis plan, P < .01 was considered statistically significant to limit the risk of false-positive results. All analyses were performed using SAS software, version 8.2 (SAS Institute, Cary, NC).
Cell Cycle Regulators and Patient Characteristics We assessed immunostaining of the biomarkers in tumor sections of 783 patients. After exclusion of patients without valid internal positive controls, 778 patients remained in the study, and all further statistical analyses were based on these patients. These 778 patients were also representative of the participating centers’ populations because the pre–random assignment characteristics and overall survivals of the patients who were included in the present study did not differ from those of patients from the same centers who were not included (data not shown). The immunohistochemistry score distributions of the six markers and their median values are shown in Figure 1. These median scores defined marker-positive patients and marker-negative patients and were used to study the relationship of the biomarkers with clinical and laboratory parameters. The association of p27Kip1 with clinical variables is shown in Table 1. High levels of p27Kip1 were more frequently observed in low lymphoid infiltrated tumors (P = .05), but otherwise, p27Kip1 was not significantly associated with any other clinical parameter listed in Table 1. In addition, we compared baseline data according to the status of the respective biomarker with multivariate logistic models. The marker positivity was studied simultaneously according to age, sex, tumor status, nodal status, pathologic tumor stage, histologic type, WHO performance status, and lymphoid infiltration. In these analyses, p27Kip1 positivity was associated with low lymphoid-infiltrated tumors (P = .05). Females and patients with adenocarcinomas were more frequently positive for p16INK4A (P = .002 and P < .001, respectively). Expression of cyclin D3 was associated with higher nodal status (P = .04). Patients with adenocarcinomas were more frequently negative for cyclin E (P < .001). Pathologic tumor stage III (P = .007) was associated with Ki-67 positivity, whereas adenocarcinomas (P < .001) and the tumors of patients with a WHO performance status of 1 (P = .005) were more frequently Ki-67 negative.
Next, we examined the relationship between the cell cycle regulator scores and considered them related when the absolute value of the correlation coefficient was above 0.2 (Appendix Table A2, online only). Interestingly, p27Kip1, cyclin D1, and cyclin D3 were all pair-wise correlated. In addition, cyclin E was correlated with Ki-67. These correlations were all significant (P < .001), but none of the correlation coefficients was greater than 0.36. Furthermore, the principal component analysis did not reveal any redundancy between the markers.
Prognostic Analysis
Predictive Analysis There was a relationship between p27Kip1 status and benefit of cisplatin-based chemotherapy (test for interaction, P = .02; Tables 3 and 4). Among patients with p27Kip1-negative tumors, patients who were treated with cisplatin-based chemotherapy had a longer overall survival time than patients from the control group (adjusted HR for death = 0.66; 95% CI, 0.50 to 0.88; P = .006). In patients with p27Kip1-positive tumors, the overall survival was not different between patients treated with cisplatin-based chemotherapy and controls (adjusted HR for death = 1.09; 95% CI, 0.82 to 1.45; P = .54; Table 4). Furthermore, in p27Kip1-negative patients, the median overall survival time was 13 months longer in the chemotherapy group compared with the control group (58 and 45 months, respectively; Table 4, Fig 2A). Comparable results were obtained when the p27Kip1 score was analyzed as a continuous variable (test for trend, P = .03). When the analysis is focused on the chemotherapy arm, patients with p27Kip1-positive tumors experienced a shorter overall survival compared with patients with p27Kip1-negative tumors (adjusted HR for death = 1.35; 95% CI, 1.02 to 1.80; P = .04; Table 4). Disease-free survival in patients with p27Kip1-negative tumors was also higher in the chemotherapy group compared with the control group (adjusted HR for recurrence or death = 0.71; 95% CI, 0.54 to 0.94; P = .02), but the test for interaction between p27Kip1 expression and treatment on disease-free survival was of marginal statistical significance (P = .07). In contrast to p27Kip1, the other cell cycle regulators and Ki-67 did not predict benefit of adjuvant cisplatin-based chemotherapy (Table 3). Thus, NSCLC patients with p27Kip1-negative tumors benefit from adjuvant cisplatin-based chemotherapy after complete tumor resection.
Several large randomized studies, including IALT, have demonstrated that adjuvant cisplatin-based chemotherapy improves survival of patients with completely resected NSCLC.3,5,6 Because the benefit of adjuvant chemotherapy is limited to a subgroup of patients, characterization of these patients would be of major clinical relevance. In the current study, we demonstrated that p27Kip1 status is of predictive value with regard to the outcome of adjuvant chemotherapy. Patients with p27Kip1-negative tumors benefited from adjuvant cisplatin-based chemotherapy, whereas patients with p27Kip1-positive tumors did not. These results are consistent with in vitro studies that suggested that overexpression of p27Kip1 is associated with resistance to anticancer drugs.10,12,13 Upregulation of p27Kip1 mediates drug resistance both in tumor cells grown as spheroids or confluent monolayers and in human leukemic cells grown in suspension,10,12,13 whereas downregulation of p27Kip1 expression by antisense oligonucleotides reduces intercellular adhesion, increases cell proliferation, and enhances drug sensitivity of tumor cells grown as multicellular spheroids.10
As a member of the cyclin-dependent kinase inhibitory proteins, p27Kip1 prevents retinoblastoma protein phosphorylation and subsequent G1 Our data could have several clinical implications. First, p27Kip1 may be a marker for the selection of patients for adjuvant chemotherapy in the future. Before widespread clinical use, however, confirmatory studies on other adjuvant study populations are warranted. Second, p27Kip1 should be studied as predictor of outcome of palliative chemotherapy. Third, p27Kip1 should be considered as a stratification factor in future adjuvant chemotherapy trials. Finally, modulation of p27Kip1 could be a strategy to improve outcome of adjuvant chemotherapy in NSCLC. This approach is supported by in vitro studies that demonstrated that antagonists of p27Kip1 may be useful chemotherapy sensitizers in combination with conventional chemotherapy.17 This study was conducted according to a detailed protocol (available on request from the authors) that stressed the importance of collecting most of the tumor specimens within the participating centers, required a large sample size to ensure adequate power both for prognostic and predictive analyses, and specified a statistical plan of analysis. Adjusting on standard prognostic variables and specifying an objective cutoff point for defining positivity strengthen the reported results.18 We have prospectively chosen the median value of the immunohistochemistry score as the cutoff point to discriminate between marker-positive and marker-negative patients. Although the median may not be the only appropriate value, it has two advantages. First, it is an objective and unbiased value and not determined after the fact as an optimal cutoff point; therefore, P value adjustments and questionable bias correction are not necessary. Second, maximum power for prognostic and predictive analyses is achieved when the marker is equally distributed.19 Considering the level of significance that was a priori fixed (P = .01), our result concerning p27Kip1 is only borderline significant (P = .02). Nevertheless, it is consistent with the trend relationship of p27Kip1 (P = .03) and the association with disease-free survival (P = .07). Although it was not possible to collect tumor samples for 100% of the patients within centers, the 83% of patients included did not differ from the 17% not included. Another predictor of the benefit of adjuvant chemotherapy was recently shown to be the excision repair cross-complementation group 1 enzyme.20 Evaluation of other biomarkers and the definition of a drug resistance score obtained by a combination of the various predictive factors are ongoing. In conclusion, p27Kip1 predicts response to cisplatin-based adjuvant chemotherapy in completely resected NSCLC. Before establishing p27Kip1 as a routine marker for selection of patients for adjuvant chemotherapy, the predictive value of p27Kip1 should be confirmed by independent studies.
The author(s) indicated no potential conflicts of interest.
Conception and design: Martin Filipits, Robert Pirker, Ariane Dunant, Fabrice André, Rolf Stahel, Jean-Pierre Pignon, Jean-Charles Soria, Helmut H. Popper, Thierry Le Chevalier, Elisabeth Brambilla Financial support: Martin Filipits, Robert Pirker, Ariane Dunant, Fabrice André, Rolf Stahel, Jean-Pierre Pignon, Jean-Charles Soria, Helmut H. Popper, Thierry Le Chevalier, Elisabeth Brambilla Administrative support: Martin Filipits, Robert Pirker Provision of study materials or patients: Martin Filipits, Robert Pirker, Helmut H. Popper, Thierry Le Chevalier, Elisabeth Brambilla Collection and assembly of data: Martin Filipits, Robert Pirker, Ariane Dunant, Sylvie Lantuejoul, Katharina Schmid, Anh Huynh, Fabrice André, Jean-Pierre Pignon, Elisabeth Brambilla Data analysis and interpretation: Martin Filipits, Robert Pirker, Ariane Dunant, Sylvie Lantuejoul, Katharina Schmid, Anh Huynh, Vincent Haddad, Fabrice André, Rolf Stahel, Jean-Pierre Pignon, Jean-Charles Soria, Helmut H. Popper, Thierry Le Chevalier, Elisabeth Brambilla Manuscript writing: Martin Filipits, Robert Pirker, Ariane Dunant, Vincent Haddad, Jean-Pierre Pignon, Jean-Charles Soria, Helmut H. Popper, Elisabeth Brambilla Final approval of manuscript: Martin Filipits, Robert Pirker, Ariane Dunant, Sylvie Lantuejoul, Katharina Schmid, Anh Huynh, Vincent Haddad, Fabrice André, Rolf Stahel, Jean-Pierre Pignon, Jean-Charles Soria, Helmut H. Popper, Thierry Le Chevalier, Elisabeth Brambilla
The following investigators, pathologists, and centers participated in the International Adjuvant Lung Cancer Trial Biologic Program: Austria: R. Pirker, Department of Medicine I, Vienna; G. Dekan, Institute of Clinical Pathology, Vienna; Belgium: J. Vansteenkiste, University Hospital, Leuven; Brazil: I. Sathler Pinel, Instituto Nacional de Cancer, Rio de Janeiro; R. Younes, Hospital A.C. Camarco, Sao Paulo; France: A.A. Kanoui, Centre Physiothérapie du Rouget, Sarcelles; R. Dachez, Laboratoire L.C.L., Paris; S. Deslignères, Hospital Delafontaine, Saint-Denis; O. Languille-Mimoune, Cabinet Pathologie, Paris; P. Sabatier, Centre Hospitalier Victor Dupouy, Argenteuil; T. Le Chevalier, Institut Gustave-Roussy, Villejuif; M. Antoine, Hôpital Tenon, Paris; P. Boz, Cabinet de Pathologie, Papeete; P. Bruneval, Association Promotion Anatomie Pathologique, Paris; M.C. Charpentier, Cabinet Pathologie Tolbiac, Paris; B. Chetaille, Hôpital Sainte Marguerite, Marseille; E. Dulmet, Centre Chirurgical Marie-Lannelongue, Le Plessis Robinson; F. Capron, Groupe Hospitalier Pitié-Salpétrière, Paris; B. Gosselin, Centre Hospitalier Universitaire (CHU), Lille; D. Grunenwald, P. Validire, Institut Mutualiste Montsouris, Paris; F. Labrousse, CHU, Limoges; N. Pericoli, Roma (Italy); D. Petrot, Cabinet d'Anatomie Pathologique, Niort; N. Rouyer, Cabinet de Pathologie Butet-Rouyer, Nice; B. Milleron, M. Antoine, Hôpital Tenon, Paris; J.F. Morère, M.A. Kambouchner, Hôpital Avicenne, Bobigny; G. Ozenne, Ceditrac–CMC du Cèdre, Bois Guillaume; T. Ducastelle, Laboratoire d'Anatomie et Cytologie, Rouen; E. Quoix, Hôpital Lyautey, Strasbourg; P. Durand de Grossouvre, Laboratoire d'Anatomie Pathologique, Haguenau; B. Gasser, C.H.U., Strasbourg; A. Rivière, Centre François Baclesse, Caen; F. Galateau-Salle, CHU, Caen; C. Tuchais, P. Jallet, G. Bertrand, I. Valo, Centre Paul Papin, Angers; Germany: W. Eberhardt, University Hospital, Essen; D. Theegarten, Institute of Pathology, Ruhr-University Bochum, Bochum; Greece: P. Christaki, Papanikolaou General Hospital, Pylea; T. Dosios, V. Kyriakou, Athens University School of Medicine, Athens; E. Papadakis, P. Agelidou, Sotiria Hospital, Athens; K. Zarogoulidis, University Hospital, Thessaloniki; Italy: A. Masotti, Azienda Ospedaliera Di Verona, Verona; Lithuania: A. Jackevicius, Institute of Oncology Vilnius University, Vilnius; Poland: J. Laudanski, L. Chyczewski, M. Kozlowski, J. Niklinski, Medical School, Bialystok; T. Grodski, J. Pankowski, Regional Hosp. for Lung Diseases, Szczecin; T. Orlowski, M. Chabowski, R. Langfort, Institute of Tuberculosis and Lung Disease, Warsaw; B. Muszczynska-Bernhard, Dolnoslaskiego Centrum Chorob Pluc, Wroclaw; Romania: T. Ciuleanu, Oncological Institute "Ion Chiricuta," Cluj-Napoca; Slovakia: J. Baumohl, University Teach. Hospital, Kosice; Spain: F. Cardenal, Hospital Duran I Reynals, Barcelona; R. Bernat, Hospital de Bellvitge, Barcelona; J. Salinas, J.B. Lopez, Hospital Virgen de Arrixaca, El Palmar Murcia; Sweden: B. Bergman, A. Hussein, Sahlgrenska Hospital, Göteborg; and Yugoslavia: G. Radosavljevic, Institute for Lung Disease, Belgrade.
Supported by the Austrian Federal Ministry of Education, Science and Culture (Grant No. GZ 200.062/2-VI/1/2002), the Austrian Science Fund (Grant No. P15377), Programme Hospitalier de Recherche Clinique, Cancéropôle Rhône-Alpes, Institute of Pathology Graz, and an unrestricted research grant from Eli-Lilly. Authors’ disclosures of potential conflicts of interest and author contributions are found at the end of this article.
1. Non-Small Cell Lung Cancer Collaborative Group: Chemotherapy in non-small cell lung cancer: A meta-analysis using updated data on individual patients from 52 randomised clinical trials. BMJ 311:899-909, 1995 2. Scagliotti GV, Fossati R, Torri V, et al: Randomized study of adjuvant chemotherapy for completely resected stage I, II, or IIIA non-small-cell lung cancer. J Natl Cancer Inst 95:1453-1461, 2003 3. The International Adjuvant Lung Cancer Trial Collaborative Group: Cisplatin-based adjuvant chemotherapy in patients with completely resected non-small-cell lung cancer. N Engl J Med 350:351-360, 2004 4. Kato H, Ichinose Y, Ohta M, et al: A randomized trial of adjuvant chemotherapy with uracil-tegafur for adenocarcinoma of the lung. N Engl J Med 350:1713-1721, 2004 5. Winton T, Livingston R, Johnson D, et al: Vinorelbine plus cisplatin vs. observation in resected non-small-cell lung cancer. N Engl J Med 352:2589-2597, 2005 6. Douillard JY, Rosell R, De Lena M, et al: Adjuvant vinorelbine plus cisplatin versus observation in patients with completely resected stage IB-IIIA non-small-cell lung cancer (Adjuvant Navelbine International Trialist Association [ANITA]): A randomised controlled trial. Lancet Oncol 7:719-727, 2006[CrossRef][Medline] 7. Strauss GM, Herndon JE, Maddaus MA, et al: Adjuvant chemotherapy in stage IB non-small-cell lung cancer (NSCLC): Update of Cancer and Leukemia Group B (CALGB) protocol 9633. J Clin Oncol 24:365s, 2006 (abstr 7007) 8. Pignon J-P, Tribodet H, Scagliotti GV, et al: Lung Adjuvant Cisplatin Evaluation (LACE): A pooled analysis of five randomized clinical trials including 4,584 patients. J Clin Oncol 24:366s, 2006 (abstr 7008) 9. Sherr CJ: Cancer cell cycles. Science 274:1672-1677, 1996 10. St Croix B, Florenes VA, Rak JW, et al: Impact of the cyclin-dependent kinase inhibitor p27Kip1 on resistance of tumor cells to anticancer agents. Nat Med 2:1204-1210, 1996[CrossRef][Medline] 11. Schmoor C, Sauerbrei W, Schumacher M: Sample size considerations for the evaluation of prognostic factors in survival analysis. Stat Med 19:441-452, 2000[CrossRef][Medline] 12. Dimanche-Boitrel MT, Micheau O, Hammann A, et al: Contribution of the cyclin-dependent kinase inhibitor p27KIP1 to the confluence-dependent resistance of HT29 human colon carcinoma cells. Int J Cancer 77:796-802, 1998[CrossRef][Medline] 13. Eymin B, Haugg M, Droin N, et al: P27Kip1 induces drug resistance by preventing apoptosis upstream of cytochrome c release and procaspase-3 activation in leukemic cells. Oncogene 18:1411-1418, 1999[CrossRef][Medline] 14. Katayose Y, Kim M, Rakkar AN, et al: Promoting apoptosis: A novel activity associated with the cyclin-dependent kinase inhibitor p27. Cancer Res 57:5441-5445, 1997 15. Masuda A, Osada H, Yatabe Y, et al: Protective function of p27(KIP1) against apoptosis in small cell lung cancer cells in unfavorable microenvironments. Am J Pathol 158:87-96, 2001 16. Ishii T, Fujishiro M, Masuda M, et al: Effects of p27Kip1 on cell cycle status and viability in A549 lung adenocarcinoma cells. Eur Respir J 23:665-670, 2004 17. Achenbach TV, Muller R, Slater EP: Synergistic antitumor effect of chemotherapy and antisense-mediated ablation of the cell cycle inhibitor p27KIP-1. Clin Cancer Res 6:3006-3014, 2000 18. McShane LM, Altman DG, Sauerbrei W, et al: Reporting recommendations for tumor marker prognostic studies (REMARK). J Natl Cancer Inst 97:1180-1184, 2005 19. Altman DG, Lyman GH: Methodological challenges in the evaluation of prognostic factors in breast cancer. Breast Cancer Res Treat 52:289-303, 1998[CrossRef][Medline] 20. Olaussen KA, Dunant A, Fouret P, et al: DNA repair by ERCC1 in non-small-cell lung cancer and cisplatin-based adjuvant chemotherapy. N Engl J Med 355:983-991, 2006 Submitted July 18, 2006; accepted March 19, 2007. Related Editorial
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Copyright © 2007 by the American Society of Clinical Oncology, Online ISSN: 1527-7755. Print ISSN: 0732-183X
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ABSTRACT
INTRODUCTION
2 tests stratified by center, and their overall survivals were compared using a Cox model. Baseline data according to the biomarker status were compared using univariate analyses with 
) Median score. (
) Outliers. (*) Extremes.
S transition through inhibition of both cyclin D1 and cyclin E. In this regard, p27Kip1 is considered a tumor suppressor protein. Indeed, tumor cells treated with anticancer drugs are more sensitive during late G1 and G2 phase transit than when protected by a G1 or G2 checkpoint. Therefore, logically, p27Kip1-induced cell cycle arrest in G1 would protect cells from anticancer drugs. Besides its classical antiproliferative function, p27Kip1 can also promote or inhibit apoptosis according to the cellular context.
