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Journal of Clinical Oncology, Vol 26, No 16 (June 1), 2008: pp. 2690-2698
© 2008 American Society of Clinical Oncology.
DOI: 10.1200/JCO.2007.15.5580

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Predictive Biomarkers of Chemotherapy Efficacy in Colorectal Cancer: Results From the UK MRC FOCUS Trial

Michael S. Braun, Susan D. Richman, Philip Quirke, Catherine Daly, Julian W. Adlard, Faye Elliott, Jennifer H. Barrett, Peter Selby, Angela M. Meade, Richard J. Stephens, Mahesh K.B. Parmar, Matthew T. Seymour

From the Leeds Institute of Molecular Medicine and St James's Institute of Oncology, University of Leeds; the National Cancer Research Institute Colorectal Clinical Studies Group; and the Medical Research Council Clinical Trials Unit, London, United Kingdom

Corresponding author: Matt Seymour, MA, MD, FRCP, St James's Institute of Oncology, St James's University Hospital, Leeds LS9 7TF, United Kingdom; e-mail: matt.seymour{at}leedsth.nhs.uk


    ABSTRACT
 TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
 AUTHORS' DISCLOSURES OF...
 AUTHOR CONTRIBUTIONS
 Appendix
 REFERENCES
 
Purpose Candidate predictive biomarkers for irinotecan and oxaliplatin were assessed in 1,628 patients in Fluorouracil, Oxaliplatin, CPT-11: Use and Sequencing (FOCUS), a large randomized trial of fluorouracil alone compared with fluorouracil and irinotecan and compared with fluorouracil and oxaliplatin in advanced colorectal cancer.

Methods The candidate biomarkers were: tumor immunohistochemistry for MLH1/MSH2, p53, topoisomerase-1 (Topo1), excision repair cross-complementing gene 1 (ERCC1), O-6-methylguanine-DNA-methyltranserase (MGMT), and cyclooxygenase 2 (COX2); germline DNA polymorphisms in GSTP1, ABCB1, XRCC1, ERCC2, and UGT1A1. These were screened in more than 750 patients for interaction with benefit from irinotecan or oxaliplatin; two markers (Topo1 and MLH1/MSH2) met criteria to be taken forward for analysis in the full population. Primary end points were progression-free survival (PFS) and overall survival.

Results One thousand three hundred thirteen patients (81%) were assessable for Topo1 immunohistochemistry (low, < 10%; moderate, 10% to 50%; or high, > 50% tumor nuclei). In patients with low Topo1, PFS was not improved by the addition of either irinotecan (hazard ratio [HR], 0.98; 95% CI, 0.78 to 1.22) or oxaliplatin (HR, 0.85; 95% CI, 0.68 to 1.07); conversely, patients with moderate/high Topo1 benefited from the addition of either drug (HR, 0.48 to 0.70 in all categories; interaction P = .005; overall, P = .001 for irinotecan; P = .05 for oxaliplatin). High Topo1 was associated with a major overall survival benefit with first-line combination chemotherapy (HR, 0.60; median benefit, 5.3 months); patients with moderate or low Topo1 did not benefit (HR, 0.92 and 1.09, respectively; interaction P = .005). MLH1/MSH2 did not show significant interaction with treatment, although the low rate of loss (4.4%) limits the power of the study for this biomarker.

Conclusion Topo1 immunohistochemistry identified subpopulations that did or did not benefit from irinotecan, and possibly also from oxaliplatin. If verified independently, this information will contribute to the individualization of treatment for colorectal cancer.


    INTRODUCTION
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 ABSTRACT
 INTRODUCTION
 METHODS
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 AUTHORS' DISCLOSURES OF...
 AUTHOR CONTRIBUTIONS
 Appendix
 REFERENCES
 
Recent years have seen significantly improved outcomes for patients with colorectal cancer, largely thanks to improved drug therapy. Options have expanded from just one—fluorouracil (FU)—to include irinotecan, oxaliplatin, oral fluoropyrimidines, and targeted agents against epidermal growth factor receptor and vascular endothelial growth factor. More agents are well along the development pipeline.

The average incremental benefit accruing from each new drug may be modest1,2 but small averages might conceal subpopulations of patients who benefit greatly. Conversely, others may gain nothing from a drug, but still incur toxicity while foregoing more worthwhile alternatives. Predicting the effectiveness of individual treatments for individual patients could therefore greatly improve cancer care. It might also bring active new drugs within the scope of populations from whom they are currently totally excluded for financial reasons.3

Biomarkers correlating with patient outcomes (such as survival or progression) are categorized as prognostic or predictive.4 Prognostic biomarkers correlate with outcome independent of treatment. They may be ascertained through studies of consistently-treated or untreated patients. Many prognostic biomarkers have been described in colorectal cancer, including aneuploidy5,6 and p53.7 Their chief shortcoming is that they do not predict whether the patient's outcome —good or bad— will be improved by treatment. Therefore, except in extreme cases, prognostic biomarkers have limited impact on treatment choices.

Predictive biomarkers correlate with the impact of specific treatments on outcome. They are of greater potential clinical usefulness, but much more difficult to ascertain. Studies in nonrandomized populations are unlikely to detect predictive markers reliably, since they cannot distinguish whether differing outcomes are due to underlying tumor behavior or to the impact of treatment. This distinction requires a trial in which the drug in question has been subjected to randomization; furthermore the trial must be large, to allow treatment impact to be assessed separately, and compared across subgroups of patients of different biomarker status.

To our knowledge, Fluorouracil, Oxaliplatin, CPT-11: Use and Sequencing (FOCUS)8 is the largest randomized trial yet reported in metastatic colorectal cancer. It included randomization to first-line therapy with single-agent FU, or FU plus irinotecan or oxaliplatin. It included a prospectively planned predictive biomarker study, providing an ideal resource to evaluate predictive markers for irinotecan and oxaliplatin. We report the first results, evaluating 11 biomarkers previously proposed in smaller studies.


    METHODS
 TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
 AUTHORS' DISCLOSURES OF...
 AUTHOR CONTRIBUTIONS
 Appendix
 REFERENCES
 
The FOCUS Trial
FOCUS has been reported in detail elsewhere.8 Two thousand one hundred thirty-five patients with newly presenting metastatic colorectal cancer were randomly assigned from 2000 to 2003. Separate consent was requested for access to stored histopathological specimens. Multicenter ethical approval was obtained. The trial was managed by the Medical Research Council Clinical Trials Unit, overseen by an independent trial steering committee which also prospectively approved the molecular analysis plan.

Trial design is illustrated in Figure 1.8-11 Patients allocated to strategies A and B received sequential therapy, starting with FU alone, while strategy C patients received first-line combination chemotherapy—FU plus either irinotecan or oxaliplatin. The clinical report contains full details of patient characteristics, treatment schedules, and clinical outcomes.8 The main focus of this biomarker study is the contribution of irinotecan or oxaliplatin to first-line therapy, assessed by comparison of progression-free survival (PFS) in strategy A or B versus C with irinotecan or C with oxaliplatin.


Figure 1
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Fig 1. The Fluorouracil, Oxaliplatin, CPT-11: Use and Sequencing (FOCUS) clinical trial design. For full details, see Seymour et al.8 Randomization was equal among the three strategies (A, B, C), with B and C equally subdivided to irinotecan (ir) and oxaliplatin (ox) groups, giving five arms in 2:1:1:1:1 ratio. Fluorouracil (FU), alone or in combination, was with modified de Gramont regimens;9-11 single-agent ir was given once every 3 weeks. (*) In the sequential strategies, second-line treatment after progression on FU was: in arm A, single-agent ir; in arm B-ir, ir + FU; in arm B-ox, ox + FU.

 
Molecular Assessments
Formalin-fixed, paraffin-embedded tumor specimens were retrieved from 1,628 patients as shown in Figure 2. Samples were anonymized by the trials unit, then forwarded to the laboratory, which was blind to treatment and outcomes. Tumor tissue was identified and sections were cut for DNA extraction. Tissue microarrays were constructed, containing one normal and three tumor 0.6 mm cores per patient.


Figure 2
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Fig 2. CONSORT diagram. FOCUS, Fluorouracil, Oxaliplatin, CPT-11: Use and Sequencing trial; FU, Fluorouracil; ir, irinotecan; ox, oxaliplatin; Topo1, topoisomerase-1; IHC, immunohistochemistry; OS, overall survival; PFS, progression-free survival.

 
We studied 11 candidate predictive biomarkers of irinotecan and/or oxaliplatin efficacy. Six were assessed by tumor immunohistochemistry: excision repair cross-complementing gene 1 (ERCC1)12; topoisomerase-1 (Topo1)13; p5314; O-6-methylguanine-DNA-methyltranserase (MGMT)15; cyclooxygenase 2 (COX2),16 and immunohistochemical assessment of mismatch repair17 (MLH1/MSH2 both present v either absent, previously validated in our laboratory17). Germline single nucleotide polymorphisms were assessed in four genes: glutathione-S-transferase-P1 (GSTP1) A313G18; ATP-binding-cassette-group-B, gene 1 (ABCB1) C3435T19,20; x-ray-cross-complementing-group 1 (XRCC1) Q399R21,22; and ERCC2 K751Q.23 A variable-number tandem-repeat promoter polymorphism was assessed in UDP-glucuronyltransferase (UGT1A1*28).24,25

Assay Methods
For immunohistochemistry, 5-µm sections of tissue microarrays or whole sections were stained as detailed in Table 1. Antigen retrieval was performed by pressure cooking in 1% Vector Ag retrieval solution (Vector Laboratories, Burlingame, CA), or 10 mmol/L citrate buffer pH 6 for Topo1. Protein expression was assessed using Envision (DAKO, Ely, UK), ChemMate (DAKO), or Avidin-Biotin peroxidase (ABC Kit, DAKO). Scoring was performed independently by two observers using cutpoints defined prospectively based on previous literature. Discordant cases were reviewed jointly.


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Table 1. Protein Immunohistochemistry Conditions

 
DNA was extracted from macrodissected normal tissue (or tumor, if none available) using proteinase K digestion, phenol/chloroform/isoamyl alcohol (25:24:1), and ethanol precipitation. Single nucleotide polymorphisms were assessed using primer/probe sequences listed in Table 2. Each 25-µL reaction contained 50 ng DNA, 15 pmol each primer, 10 pmol each TaqMan probe (Applied Biosystems, Foster City, CA) and Universal Master Mix (Applied Biosystems). Reaction plates were run on an Applied Biosystems 9700 thermocycler (95°C x10 minutes, then 40 cycles of 92°C x15 seconds, 60°C x1 minute) and read using an Applied Biosystems 7700 sequence detector.


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Table 2. DNA Polymorphism Assays

 
UGT1A1*28 VNTR was assessed by polymerase chain reaction and polyacrylamide gel electrophoresis. Each reaction contained: 3 pmol Fam-labeled forward primer; 15 pmol unlabeled reverse primer; 15 mmol/L MgCl2; 0.25 mmol/L dNTPs; 1 unit Thermoprime; and Thermoprime buffer. Reaction conditions were: 95°C x 5 minutes; 56°C x 2 minutes; 72°C x 1 minute, then 40 cycles of 95°C x 30 seconds; 56°C x 1 minute; 72°C x3 0 seconds. Products were identified using an Applied Biosystems 377 DNA sequencer.

Statistical Analysis
FOCUS, although exceptionally large, was insufficient to split into adequately powered training and validation sets. Instead, we used FOCUS as a single, well-powered training set, from which positive findings will require independent validation.

A two-stage screen and full population approach was used. Midway through sample retrieval, available material was used to screen all 11 candidate biomarkers and exclude from further study those with no suggestion of predictive value (ie, those with adequate minor group frequencies [> 10%] showing no interaction at the 5% significance level). For markers showing interaction at P < .05 at the screen stage, or with an infrequent minor group (< 10%), all available material was collected, and analysis was performed in this full population.

This approach makes efficient use of laboratory resources and maximizes the sample size for markers of interest. Please note that because the full population includes patients used in the screen, it does not constitute independent verification.

At the time of screen analysis, confirmed radiological data were not yet available for all patients, so a clinically-determined end point was used—time to treatment failure (TTF; time from randomization to clinical decision to start second-line therapy or permanently discontinue first-line therapy, or death). The screen data set was later reanalyzed using the standard end point PFS (randomization to first evidence of tumor progression or death) to confirm that no markers had been inappropriately rejected. By the time of full population analysis, trial data collection was complete so PFS was used. Finally, overall survival (OS; randomization to death) was used to assess whether any biomarker predictive for PFS would also identify patients gaining survival benefit from first-line combination therapy (strategy C) compared with staged therapy (strategies A and B).

Kaplan-Meier curves were plotted and Cox proportional hazards models used to estimate hazard ratios (HRs) and 95% CI for treatment received, stratified by marker status. Interactions between treatment effects and biomarkers were tested using the likelihood ratio (comparing a model including interaction terms for each treatment/biomarker combination with a model including only main effects).

Biomarkers showing predictive effects were also assessed as prognostic factors in patients treated with FU alone, using simple and multivariable Cox proportional hazards modeling of the effect of the biomarker on PFS, adjusting for other factors previously shown to be prognostic in this population (thymidylate synthase [TS] and deoxyuridine triphosphatase [dUTPase] immunohistochemistry; presence of liver metastases; tumor grade; baseline alkaline phosphatase [ALP]).26 Combined effects of predictive and prognostic factors were then modeled.

Our sample size was governed by the clinical trial and efficiency of sample retrieval; within these constraints power was estimated using an approximate method.27 For example, with 1,000 patients at the screening stage, taking the rates of TTF and PFS observed in FOCUS, there is 80% power (5% significance) to correctly take forward a marker assessable in 90% of samples distinguishing groups with an incremental benefit of 6-months versus 1-month increase in TTF. At the full population stage, with around 1,500 patients' material, the same effect on PFS is detectable with more than 90% power.

As a guide to interpretation of results in the context of multiple testing, false-positive report probabilities (FPRP) were calculated according to Wacholder.28 The FPRP estimates the risk that a statistically significant interaction is false-positive, based on the observed P value, the power to detect interaction at that level and the prior probability (PP) of interaction. PP is a subjective measure, used to reflect the strength of the prior hypothesis and preceding data, but applying a range of PPs can test the robustness of any statistically positive findings.

Statistical analyses were conducted using Stata version 9 (StataCorp 2005, College Station, TX).


    RESULTS
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 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
 AUTHORS' DISCLOSURES OF...
 AUTHOR CONTRIBUTIONS
 Appendix
 REFERENCES
 
The median age was 62 years (range, 27 to 85 years); colonic:rectal primary tumors were in the ratio 66:34. These and other patient characteristics were very similar to the overall FOCUS trial population.8 Primary tumors were obtained in 96% cases, metastatic biopsies in 4%.

The screen population comprised patients whose samples had been analyzed by January 2005. The numbers assayed for each biomarker vary because some samples were insufficient for all 12 assays to be performed, and because assays were performed at different times. Thus, the numbers in the screen stage varied as presented in Table 3. The full population analysis was undertaken in January 2006, when material had been received from 1,628 patients and analyzed in 1,313 to 1,351 cases.


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Table 3. Screen for Predictive Biomarkers: Associations Between Molecular Biomarkers and Treatment Impact Upon Time to Treatment Failure

 
Predictive Biomarkers: The Screen Analysis
In the screen analysis (Table 3), only Topo1 interacted significantly with the effect of treatment on TTF. Irinotecan or oxaliplatin did not improve TTF in patients with low Topo1, but produced major improvements in patients with moderate/high Topo1. The test for interaction (P = .03) met the criteria for Topo1 to be assessed in the full population.

Only 40 (4%) of 931 screen patients showed MLH1/MSH2 loss. There was a suggestion of increased benefit from oxaliplatin in these patients, but with such small numbers the test for interaction was not significant. MLH1/MSH2 was therefore taken forward for analysis in the full population to maximize power.

TTF is potentially affected by factors other than treatment efficacy. Therefore, when full PFS data became available, the screen analysis was repeated for all 11 markers using PFS in place of TTF. This confirmed the original findings—the interaction remained significant for Topo1 (P = .0002), but no significant interactions were seen for the other 10 candidate markers, with P values in the range .1 to .9 (data not shown).

Predictive Biomarkers: The Full Population Analysis
For the full population analysis, Topo1 was successfully assessed in 491 more cases, for a total of 1,313. MLH1/MSH2 status was assessed in a further 420 cases, giving a total of 1,351. For Topo1, analysis in the full population, using PFS, strongly reinforces the screen findings. Patients with low Topo1 gained no significant benefit from either irinotecan or oxaliplatin, while those with moderate or high Topo1 gained, respectively, intermediate or very marked benefit (Table 4).


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Table 4. Full Population Analysis for Predictive Biomarkers: Associations With Treatment Impacts Upon Progression-Free and Overall Survival

 
FPRPs were then calculated. The primary analysis had tested for interaction between Topo1 and either treatment. Even using a very conservative PP of 3%, the FPRP for the observed interaction (P = .005) was 18%, indicating that this finding is much more likely to have arisen through a true interaction than by chance.

The individual P value for Topo1/irinotecan interaction is .001; for Topo1/oxaliplatin, it is .05. Treating these separately, the study had approximately 75% power to detect interaction with one drug at the 5% level, dropping to 26% at the 0.1% level. Applying PPs for Topo1/irinotecan interaction of 5%, 10%, and 20%, the FPRPs for the significant interaction are 0.07, 0.03, and 0.02, respectively, indicating a strong likelihood that the observation reflects a true interaction. Conversely, the PP for Topo1/oxaliplatin was lower and the interaction weaker: applying PPs of 1%, 2%, and 5%, the FPRPs are 0.87, 0.77, and 0.56, respectively. The observed interaction with oxaliplatin is thus more likely to have arisen by chance.

MLH1/MSH2 loss was present in only 4.4% percent of patients. There was no significant interaction between MLH1/MSH2 loss and treatment effect on PFS in the full population (P = .7).

Predictive/Prognostic Interaction Model
Having established its predictive effects, Topo1 was assessed as a prognostic marker by comparing PFS by Topo1 status in the 848 patients receiving first-line FU alone. Higher Topo1 correlated with worse outcome. In univariate analysis, compared with low Topo1, the HR with moderate Topo1 was 1.31 (95% CI, 1.12 to 1.52), and with high Topo1 was 1.38 (95% CI, 1.14 to 1.68).

Topo1 expression was then modeled with the known prognostic factors TS, dUTPase, tumor grade, liver metastases, and ALP.23 Higher Topo1 correlated with higher TS ({chi}2(2 degrees of freedom [df]) = 25.5; P < .001), and higher grade ({chi}2(2 df) = 6.8; P = .03), but TS and grade were not significantly associated with each other ({chi}2(2 df) = 1.8; P = .4). Table 5 presents a model correcting for these factors and illustrating the combined predictive and prognostic effects of Topo1. Increasing expression is associated with worse outcomes with FU alone but increasing benefit from the addition of a second drug.


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Table 5. Combined Predictive and Prognostic Effects of Topoisomerase-1 Upon Progression-Free Survival (corrected for other clinicopathologic prognostic variables)

 
Overall Survival
Patients with low or moderate Topo1 expression derived no significant survival benefit from first-line combination chemotherapy compared with the sequential strategy (Fig 3). However, patients with high Topo1 had a major improvement in OS with first-line combination chemotherapy, corresponding to a median survival advantage of 5.3 months. This interaction is highly significant (P interaction .005).


Figure 3
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Fig 3. Overall survival (OS) by treatment strategy and topoisomerase-1 (Topo1) expression. Kaplan-Meier curves showing OS by treatment strategy, according to Topo1 expression. In each panel, the solid line is sequential therapy starting with fluorouracil alone (strategy A or B); the dashed line is first-line combination chemotherapy (strategy C). Test for interaction, P = .005.

 
There was a suggestion of better OS with first-line combination therapy in patients with MLH1/MSH2 loss (HR, 0.66); however, with the small numbers in this subgroup, this finding was not statistically significant (Table 4).


    DISCUSSION
 TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
 AUTHORS' DISCLOSURES OF...
 AUTHOR CONTRIBUTIONS
 Appendix
 REFERENCES
 
FOCUS is the largest randomized trial yet to have incorporated a prospective search for predictive biomarkers in colorectal cancer, and the first examining Topo1. The randomization to FU alone or with either irinotecan or oxaliplatin was particularly valuable for this enquiry.

Topo1 was both a predictive marker associated with the benefit of either irinotecan or oxaliplatin, and a prognostic marker associated with outcomes with FU therapy alone. Patients with low Topo1 fared relatively well with first-line FU, but did not benefit from either additional drug in terms of PFS, and obtained no survival benefit from first-line combination chemotherapy. With increasing Topo1, the outcome with FU alone was worse, but the addition of a second drug became worthwhile, with a major improvement in survival for the highest expressing patients.

Topo1, as the molecular target of SN38, is a plausible predictive marker for irinotecan. Overexpression has been reported in 43% to 51% of colorectal cancers.29,30 Low expression predicted camptothecin resistance in preclinical models,31 but previous nonrandomized clinical series did not confirm this link.30,32,33 This is not inconsistent with our data, since the combination of a good prognostic and bad predictive marker is not detectable in nonrandomized studies.

The predictive association of Topo1 with oxaliplatin is interesting but unexpected and statistically weaker than with irinotecan, so should be interpreted with caution. No previous studies have assessed this interaction; however, cisplatin DNA complexes can act as Topo1 poisons, and cisplatin sensitivity increases with raised Topo1 expression.34 Genomic gain of 20q11-13, involving Topo1,35 E2F1, BCL2L1, and ZNF217, is reported in more than 50% of colorectal tumors,36-38 and Topo1 copy number correlates with Topo1 protein expression in cell lines.13 It is possible, however, that Topo1 immunohistochemistry in our study is reflecting generalized 20q-gain including unidentified determinants of oxaliplatin sensitivity. Coamplification of E2F1, a transcription factor for TS, may also explain our observed association between TS and Topo1 expression, and the finding that lower Topo1 expression, like low TS expression, is a good prognostic factor in patients receiving FU alone.26,39

Only 4.4% patients had loss of MLH1/MSH2, far lower than the rate of microsatellite instability reported in primary colon cancer series.40 However, patients with microsatellite instability high colon cancer are less likely to relapse and require palliative chemotherapy, and 34% of our population had primary rectal cancer. We were not able to confirm increased oxaliplatin sensitivity in MLH1/MSH2-negative patients. Other important negative findings of our study are the failure to validate ERCC2 and other candidates which had previously shown promise in smaller series.20

As well as predicting the effect of treatment on first-line PFS, we found that Topo1 predicts the impact of treatment strategy on OS (Fig 3). In FOCUS as a whole, survival with staged therapy was noninferior to first-line combination. However, 35% patients on the staged plans—mainly those with primary FU resistance—died without receiving further chemotherapy after first-line FU.8 Patients with high Topo1 allocated to staged strategies will have had shorter PFS on single-agent FU (Table 5) and may therefore have died without receiving the drugs to which they may have responded. Conversely, Topo1 low patients allocated to staged strategies will have benefited from optimum FU therapy, not compromised by dose reductions or interruptions due to oxaliplatin or irinotecan, with consequently longer survival.

It is important to stress that before clinical application any biomarker must be independently validated. Our FPRP estimates indicate that, despite reaching statistical significance, there remains a possibility of false positive results, especially in the case of oxaliplatin. Work is underway to validate our findings using tumor samples from the Dutch Colorectal Cancer Group Capecitabine, Irinotecan and Oxaliplatin (CAIRO) trial, which randomly assigned patients to fluoropyrimidine alone or with irinotecan,41 and FOCUS2 which compared fluoropyrimidine alone or with oxaliplatin.42 Meanwhile a recent report from a controlled trial of panitumumab in chemoresistant colorectal cancer has suggested that K-ras status may be a predictive biomarker for benefit from anti-epidermal growth factor receptor targeted therapy.43 Plans are now underway for FOCUS-3, incorporating both Topo1 and K-ras testing in a prospective randomized comparison of molecular-guided or standard therapy.

If confirmed, the findings reported herein represent the first steps toward personalized chemotherapy for colorectal cancer based on robust randomized trial data. Such investigations require material from large trials, and present major challenges,4 but are necessary and worthwhile given the huge potential benefits to patients offered by personalized treatment.


    AUTHORS' DISCLOSURES OF POTENTIAL CONFLICTS OF INTEREST
 TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
 AUTHORS' DISCLOSURES OF...
 AUTHOR CONTRIBUTIONS
 Appendix
 REFERENCES
 
Although all authors completed the disclosure declaration, the following author(s) indicated a financial or other interest that is relevant to the subject matter under consideration in this article. Certain relationships marked with a "U" are those for which no compensation was received; those relationships marked with a "C" were compensated. For a detailed description of the disclosure categories, or for more information about ASCO's conflict of interest policy, please refer to the Author Disclosure Declaration and the Disclosures of Potential Conflicts of Interest section in Information for Contributors.

Employment or Leadership Position: None Consultant or Advisory Role: None Stock Ownership: None Honoraria: None Research Funding: Richard J. Stephens, Medical Research Council; Mahesh K.B. Parmar, Medical Research Council Expert Testimony: None Other Remuneration: Mahesh K.B. Parmar, Sanofi-aventis


    AUTHOR CONTRIBUTIONS
 TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
 AUTHORS' DISCLOSURES OF...
 AUTHOR CONTRIBUTIONS
 Appendix
 REFERENCES
 
Conception and design: Michael S. Braun, Philip Quirke, Matthew T. Seymour

Collection and assembly of data: Michael S. Braun, Susan D. Richman, Catherine Daly, Julian W. Adlard, Angela M. Meade, Richard J. Stephens

Data analysis and interpretation: Michael S. Braun, Susan D. Richman, Philip Quirke, Julian W. Adlard, Faye Elliot, Jennifer H. Barrett, Mahesh K.B. Parmar, Matthew T. Seymour

Manuscript writing: Michael S. Braun, Faye Elliot, Jennifer H. Barrett, Matthew T. Seymour

Final approval of manuscript: Michael S. Braun, Philip Quirke, Julian W. Adlard, Faye Elliot, Jennifer H. Barrett, Peter Selby, Angela M. Meade, Richard J. Stephens, Mahesh K.B. Parmar, Matthew T. Seymour


    Appendix
 TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
 AUTHORS' DISCLOSURES OF...
 AUTHOR CONTRIBUTIONS
 Appendix
 REFERENCES
 
Clinical Trial Management Group.
M.T. Seymour (chair), T.S. Maughan, J. Ledermann, C. Topham, R. James, S.J. Gwyther, C. Button, D. Blake, J. Smith, M. Sculpher.

MRC Clinical Trials Unit.
S. Beall, C. Chung, S. Clawson, T. Cullum, G. Griffiths, S. Hassan, C. Johnson, B. May, A. Meade, C. Murphy, J. Nuttall, M.K.B. Parmar, J. Pickering, R.J. Stephens, L. Thompson, L. van Dyck.

Data Monitoring Committee.
J. Northover (chair), J. Brown, J.L. Mansi, M. Aapro, R. Stout.

Trial Steering Committee.
M. Mason (chair), R. Rudd, P. Johnson.

The authors wish to acknowledge the contributions of many investigators, surgeons, and histopathologists, and most especially the patients participating in the FOCUS trial, who donated their surplus pathological samples for this project. Particular thanks go to the Oncology and Pathology Departments at, and allied to, Clatterbridge Centre for Oncology (Liverpool), Velindre Hospital (Cardiff), Cheltenham General Hospital, and St Luke's Cancer Centre (Guildford) who each contributed more than 100 patients to the FOCUS molecular pathology study.

Other Contributing Centers.
United Kingdom: Addenbrooke's Hospital (Cambridge), Airedale General Hospital (Keighley), Birmingham Heartlands Hospital, Bradford Royal Infirmary, Bristol Oncology Centre, Bronglais General Hospital (Aberystwyth), Broomfield Hospital (Chelmsford), Charing Cross Hospital (London), Christie Hospital (Manchester), Churchill Hospital (Oxford), Conquest Hospital (St Leonards on Sea), Cookridge Hospital (Leeds), Derbyshire Royal Infirmary (Derby), Derriford Hospital (Plymouth), Diana Princess of Wales Hospital (Grimsby), Eastbourne District General, Essex County Hospital, Glan Clwyd Hospital (Rhyl), Glasgow Royal Infirmary, Good Hope Hospital (Sutton Coldfield), Hairmyres Hospital (East Kilbride), Hammersmith Hospital (London), Huddersfield Royal Infirmary, Ipswich Hospital, Kent & Canterbury Hospital (Canterbury), Kidderminster Hospital, Maidstone Hospital, Manor Hospital (Walsall), Middlesex Hospital (London), Mount Vernon Cancer Centre (Northwood), New Cross Hospital (Wolverhampton), North Middlesex Hospital (London), North Staffordshire Royal Infirmary (Stoke on Trent), Northamptonshire Centre for Oncology (Northampton), Oldchurch Hospital (Romford), Peterborough District Hospital, Portsmouth Oncology Centre, Princess Royal Hospital (Hull), Queen Elizabeth Hospital (Woolwich), Royal Cornwall Hospital (Truro), Royal Devon and Exeter Hospital (Exeter), Royal Free Hospital (London), Royal South Hants Hospital (Southampton), Royal Sussex County Hospital (Brighton), Russells Hall Hospital (Dudley), Salisbury District Hospital (Salisbury), Scunthorpe General Hospital, Singleton Hospital (Swansea), South Cleveland Hospital (Middlesborough), South Tyneside District Hospital (South Shields), Southend Hospital, St George's Hospital (London), St. Mary's Hospital (Isle of Wight), Staffordshire General Hospital (Stafford), Torbay Hospital; International contributor: Bank of Cyprus Oncology Centre (Cyprus).


    ACKNOWLEDGMENTS
 
We thank the patients who donated tumor material, and the many staff who assisted with its collection.


    NOTES
 
Supported by the United Kingdom Medical Research Council (FOCUS Trial, ISRCTN 79877428); Cancer Research UK; the Kaberry Fellowship, administered by the Leeds Teaching Hospitals Charitable Foundation; the Bobby Moore Research Fund, administered by Cancer Research UK; Yorkshire Cancer Research, and the Cookridge Hospital Gastrointestinal Cancer Research Unit Fund. The Medical Research Council Fluorouracil, Oxaliplatin, CPT-11: Use and Sequencing (CR08) trial was funded by the United Kingdom MRC and conducted under the auspices of the United Kingdom National Cancer Research Institute Colorectal Cancer Studies Group, with additional support from Sanofi-Synthelabo, Rhone Poulenc Rorer/Aventis Pharma, Baxter, and Wyeth.

M.S.B. and S.D.R. contributed equally to this work.

Presented in part at the 42nd Annual Meeting of the American Society of Clinical Oncology, Atlanta, GA, June 2-6, 2006.

Authors' disclosures of potential conflicts of interest and author contributions are found at the end of this article.

Clinical trial information can be found for the following: ISRCTN79877428 [controlled-trials.com] .


    REFERENCES
 TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
 AUTHORS' DISCLOSURES OF...
 AUTHOR CONTRIBUTIONS
 Appendix
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Submitted December 3, 2007; accepted March 4, 2008.


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