|
Advertisement |
|
|
||
 |
|
|||||
|
|||||
|
 |
||||||
|
||||||
|
||||||
|
Journal of Clinical Oncology, Vol 26, No 15 (May 20), 2008: pp. 2473-2481 © 2008 American Society of Clinical Oncology. DOI: 10.1200/JCO.2007.13.6424 Estrogen- and Progesterone-Receptor Status in ECOG 2197: Comparison of Immunohistochemistry by Local and Central Laboratories and Quantitative Reverse Transcription Polymerase Chain Reaction by Central Laboratory
From the Eastern Cooperative Oncology Group, Boston, MA; the University of California, San Francisco, San Francisco, CA; Genomic Health Inc, Redwood City, CA; sanofi-aventis, Bridgewater, NJ; North Central Cancer Treatment Group, Rochester, MN; Cancer and Leukemia Group B, Chicago, IL; and the Southwest Oncology Group, San Antonio, TX Corresponding author: Sunil Badve, MD, Indiana University School of Medicine, 350 West 11th St CPL-4050, Indianapolis, IN 46202; e-mail: sbadve{at}iupui.edu
Purpose: Central and local laboratory concordance for hormone receptor measurement is therapeutically important. This study compares estrogen receptor (ER) and progesterone receptor (PR) measured by local laboratory immunohistochemistry (IHC), central IHC, and central reverse-transcriptase polymerase chain reaction (RT-PCR) using a proprietary 21-gene assay. Patients and Methods: A case-control sample of 776 breast cancer patients from Eastern Cooperative Oncology Group (ECOG) study E2197 was evaluated. Central IHC Allred score for ER and PR was obtained using tissue microarrays and 1D5 ER antibody and 636 PR antibody. Quantitative RT-PCR for ER and PR in whole sections was performed using the 21-gene assay. Results: For ER, the concordance between local and central IHC was 90% (95% CI, 88% to 92%), between local IHC and central RT-PCR was 91% (95% CI, 89% to 93%), and between central IHC and central RT-PCR was 93% (95% CI, 91% to 95%). For PR, the concordance between local IHC and central IHC was 84% (95% CI, 82% to 87%), between local IHC and central RT-PCR was 88% (95% CI, 85% to 90%), and between central IHC and central RT-PCR was 90% (95% CI, 88% to 92%). Although concordance was high, IHC ER-negative cases that were RT-PCR positive were more common than IHC ER-positive cases that were RT-PCR negative. In ER-positive patients, ER expression by central IHC Allred score was marginally associated with recurrence (P = .091), and ER expression by central RT-PCR was significantly associated with recurrence (P = .014). However, recurrence score, which incorporates additional genes/pathways, was a highly significant predictor of recurrence (P < .0001). Conclusion: There is a high degree of concordance among local IHC, central IHC, and central RT-PCR by the proprietary gene assay for ER and PR status. Although ER expression is marginally associated with relapse in ER-positive patients treated with chemohormonal therapy, recurrence score is a highly significant predictor of recurrence.
Breast cancer is a heterogeneous disease with a highly variable clinical course. The discovery of hormone receptor (HR)–positive breast carcinoma was of major prognostic and therapeutic import.1 However, accurate assessment of the status of estrogen receptor (ER) and progesterone receptor (PR) remains problematic. The quantitative ligand-binding assay (LBA) was supplanted in the 1990s by immunohistochemistry (IHC).2,3 All methodologies are challenged by preanalytic and analytic variability. Preanalytic factors include fixation delay/type/duration, and protocol variations. Analytic factors include intra-/inter-observer variability and cut points with regard to percentage of cells stained and staining intensity.4 This variability may lead to inappropriate treatment decisions. Quantitative reverse-transcriptase polymerase chain reaction (RT-PCR) by Oncotype DX (Genomic Health Inc [GHI], Redwood City, CA) assay quantifies gene expression using RNA extracted from fixed, paraffin-embedded tissue.6 To evaluate the utility of standardized quantitative RT-PCR assessment of ER and PR by Oncotype DX as an alternative to IHC, we compared local and central IHC and central quantitative RT-PCR measurement of ER and PR in breast carcinomas from 776 patients.
Tumor Samples and Patient Clinical Data The Eastern Cooperative Oncology Group (ECOG) E2197 study was a prospective, randomized, clinical trial that included 2,872 assessable patients with HR-positive or -negative breast cancer and 0 to 3 positive lymph nodes.7 The protocol specified treatment with four 3-week cycles of doxorubicin (60 mg/m2) plus cyclophosphamide 600 mg/m2 (AC) or docetaxel 60 mg/m2 (AT), and hormonal therapy if HR positive. Median follow-up was 76 months. There was no relapse rate difference between treatment arms. A case-control sample of 776 patients who did (n = 179) or did not (n = 597) relapse were evaluated by the Oncotype DX assay; all relapses were selected, and a subsample of nonrelapses were controls. Paraffin blocks were reviewed by ECOG and GHI to confirm the presence of greater than 5% carcinoma. Seven samples lacked invasive carcinoma in both tissue microarray (TMA) cores but were assayed by RT-PCR: these results were excluded from the concordance analysis. Histologic subtype and grade (revised Nottingham criteria) were assessed centrally from whole tissue sections by one pathologist (F.L.B.).
Local IHC
Central IHC TMAs were reviewed centrally and scored visually by two pathologists (S.B. and F.L.B.), blinded to all clinicopathologic data, using the Allred score (AS), a method that semiquantitates the proportion of positive cells (scored on a 0 to 5 scale) and staining intensity (scored on a 0 to 3 scale), with a maximum score of 8 (AS > 2 was considered positive).3
Sample Preparation and Gene Expression Analysis Using Oncotype DX
Statistical Analysis
Agreement measures between RT-PCR and IHC include overall concordance, calculated as the number of samples that agree divided by the total number of samples, and Cox proportional hazards regression using weighted pseudo-likelihood estimation examined the associations between ER expression (IHC and RT-PCR) and relapse-free interval (RFI).15 RFI was defined as the time from entry on E2197 to the first evidence of breast cancer relapse, defined as invasive breast cancer in local, regional, or distant sites, including the ipsilateral breast, but excluding new primary breast cancers in the opposite breast. Follow-up for relapse was censored at the time of death without relapse, new primary cancer in the opposite breast, or at the time the patient was last evaluated for relapse. Five-year recurrence rates were estimated from the Cox proportional hazards regression models, on the basis of the empirical cumulative hazard estimate of the survival function. Associated 95% CIs were obtained by employing the normal theory approximation to the logarithm of the survival estimates. Analyses of time to relapse were weighted because inferences were for the full E2197 study population. All statistical tests were two sided, and P < .05 was considered significant.
Patient Characteristics A total of 776 samples are reported in the analysis of local IHC and central RT-PCR and 769 samples in the analysis of central IHC. Seven samples were nonassessable for central IHC (lack of invasive tumor in both TMA cores). Distributions of patient characteristics and tumor characteristics are in Table A1 (online only).
Distribution of ER and PR
Concordance Between IHC and RT-PCR ER concordance. Concordance was high between central IHC and central RT-PCR ER status (Table 2); positive agreement was 99% (95% CI, 98% to 100%), and negative agreement was 86% (95% CI, 82% to 89%). In the absence of a gold standard, the terms percentage of positive and percentage of negative agreement describe diagnostic accuracy as alternatives to the terms sensitivity and specificity as suggested by the US Food and Drug Administration (FDA).16
The two-by-two table for the local IHC versus central RT-PCR comparison is presented in Table 2. Positive agreement was 95% (95% CI, 93% to 97%). Negative agreement was 87% (95% CI, 83% to 90%). Between 14% (central IHC) and 13% (local IHC) of samples classified as ER negative by IHC are ER positive by central RT-PCR, whereas 1% and 5% of RT-PCR–negative cases were ER positive by local and central IHC, respectively. The distribution of AS by central IHC compared with central RT-PCR is shown in Figure 1. Although correlation exists between the measures, for the 14% of discordant cases where RT-PCR was positive and the central IHC assay by the AS was negative, the RT-PCR values were often high and not close to the 6.5 cutoff. For these discordant cases, RT-PCR measurements range from 6.5 to 10.4 units.
PR concordance. Concordance was high between central IHC and central RT-PCR PR status (Table 3); positive agreement was 85% (95% CI, 81% to 88%). Negative agreement was 96% (95% CI, 93% to 98%).
The two-by-two table for the local IHC versus central RT-PCR comparison is presented in Table 3. Positive agreement was 86% (95% CI, 81% to 89%), and negative agreement was 89% (95% CI, 86% to 92%). HR concordance. HR positivity was defined as ER and/or PR positive. Concordance between local IHC, central IHC, and central RT-PCR HR status was high (Table 4). Between 8% (central IHC) and 12% (local IHC) of samples classified as HR negative by IHC are HR positive by RT-PCR; in contrast, between 6% (central IHC) and 7% (local IHC) of samples classified as HR negative by RT-PCR are HR positive by IHC.
ER Expression and Recurrence Rates To determine the relationship between ER expression and recurrence risk, we performed the primary analysis on all study patients. A subset of patients were ER positive by local IHC, central IHC, and central RT-PCR, and were not known to have received hormonal therapy, either because hormone therapy was not given or because it was not known whether hormone therapy was given (32, 46, and 62, respectively; Table A2, online only); in a secondary analysis we excluded these patients (< 15% of the total). Figure 2 shows the relationship between central IHC AS and central RT-PCR for ER, and 5-year recurrence rates for all patients (Fig 2A) and for the subset excluding ER-positive patients who didn’t receive hormonal therapy (Fig 2B). Five-year recurrence rates are similar for the subset of patients compared with the full analysis population. When all patients were included (ER negative and ER positive), ER expression by central IHC and by central RT-PCR was statistically significant. When only ER-positive patients were analyzed, ER expression by central IHC was marginally associated with recurrence (P = .091) and central RT-PCR was significantly related to recurrence (P = .014). The pattern of 5-year recurrence rates across the seven expression categories for central IHC and central RT-PCR in Figure 2 have similar shapes; however, the CIs for lower levels of ER by AS are larger than those for lower levels of ER by RT-PCR.
For comparison, the relationship between the Oncotype DX recurrence score (RS) and recurrence risk in the subset of ER-positive patients (both node-negative and node-positive patients) was determined (Fig 3). RS was a significant predictor of recurrence (P < .0001) and was particularly effective at identifying low-risk patients, as noted by the narrow 95% CI for recurrence rate in patients with RS less than 18. Consistent with prior studies, RS was a significant predictor of recurrence (P = .0016) in the subset of node-negative patients (n = 188).9
ER Expression and RS The distribution of RS by ER expression (central IHC and central RT-PCR) was explored in ER-positive patients (Fig 4A). Although correlation between RS and ER expression was modest (correlation = –0.22 for central IHC and –0.47 central RT-PCR), there were cases with high ER expression and high RS. Similar results were obtained for node-negative and node-positive patients analyzed separately (data not shown).
Tumor Grade and RS The distribution of RS by tumor grade was explored in ER-positive patients by both central and local HC tumor grade assessment (n = 404) (Fig 4B). Although there was a strong association overall between RS and tumor grade (P < .0001 for both local and central grade), there were discrepancies. Modest agreement in assessment of histologic grade among the local and central pathologists was observed (concordance = 67% [95% CI, 63% to 70%]; weighted  = 46%; Table A3, online only).
Accurate and precise measurement of HR status is of therapeutic importance because hormonal therapy reduces the relative risk of recurrence by more than 50% in breast cancer patients with hormone-sensitive tumors.1,17,18 New methodologies for HR quantitation should be rigorously compared with the current measurement standard. In this study, there was a high level of concordance for ER, PR, and HR status between local and central IHC and central RT-PCR using the Oncotype DX assay (Table 2). The similar concordance between IHC and RT-PCR, when compared with that observed between the local and central IHC, demonstrates that quantitative RT-PCR using the Oncotype DX assay is an alternative method for determination of HR status. IHC assessment of ER and PR is recommended by the American Society of Clinical Oncology to guide breast cancer treatment.19 Unfortunately, interlaboratory variability with IHC assessment of ER/PR is relatively high in clinical practice. Rhodes et al20 showed that 80% of laboratories demonstrated ER positivity in medium-/high-expressing tumors, but only 37% demonstrated ER positivity in low-expressing tumors. There is diversity in IHC methodology. Protocol differences such as the use of antigen retrieval and the type of antigen retrieval such as pressure steam, used in this study, versus ambient steam, can contribute to variability.20 Chromogen enhancers may also be used to increase sensitivity of IHC assays (these were not employed in this study). Antibody differences are important. In a comparison of two ER antibodies, 1D5 and SP1, 8% of tamoxifen-treated patients who were SP1 positive but 1D5 negative were noted to have better clinical outcomes. A recent IHC/RT-PCR comparison study of 607 patients using SP1 showed 96% concordance between SP1 and RT-PCR by Oncotype.27 Another possible source of bias in this study was the use of two 1.0-mm cores (total area = 3.14 mm2) for HR assessment by IHC. Although this theoretically may introduce sampling bias, it is highly unlikely given that many groups have reported that three 0.6-mm cores (total area = 1.13 mm2) are highly concordant with whole tumor sections. Just as all IHC assays are not the same, nor are all RT-PCR assays the same. Differences in RNA extraction, reverse transcription, PCR protocols and machines, primer/probe selection, and reagent manufacturing can contribute to assay variability. Central lab measurement of ER and PR expression by RT-PCR using Oncotype DX employs a large number of controls and calibrators to enhance precision and reproducibility. Normalization with five reference genes addresses differences in RNA quality stemming from preanalytic factors,22,23 such as delay to fixation and duration of fixation.6,24 Cronin et al6,25 recently documented the operational performance of the standardized Oncotype DX assay: linearity over a more than 2,000-fold RNA concentration range with an average accuracy of 0.3%, coefficients of variation for the assay process below 5.7%, and assay variability contributed by instruments, operators, reagents, and day-to-day variation limited to less than 0.5 expression units (standard deviation). Although the overall concordance for ER status was high in this study, discordances that may be a result of biology (in some cases protein expression and mRNA expression may be truly different due to epigenomic factors) and/or to assay performance issues were observed. There was an imbalance in the distribution of the discordant cases between central IHC and central RT-PCR. IHC ER-negative cases that were RT-PCR positive were observed more commonly than IHC ER-positive cases that were RT-PCR negative. These discordant cases that were IHC ER negative and RT-PCR ER positive showed quantitative ER levels by RT-PCR that ranged from 6.5 to 10.5 expression units (16-fold range). In contrast, those cases that were IHC ER positive but RT-PCR negative all tended to cluster within 2 units (four-fold range) of the RT-PCR cutoff. The relatively low incidence of IHC ER-positive cases that are RT-PCR ER negative in this study is similar to the 2% discordance rate between IHC ER-positive and RT-PCR ER-negative cases seen in over 20,050 reported cases from the GHI Clinical Laboratory.26
In contrast to ER, the discordant PR cases were evenly distributed. The PR discordances are not explained by differences in PRA and PRB expression as the RT-PCR PR primer/probe set identifies both species. Finally, when either ER-positive and/or PR-positive cases were assessed as HR positive, the overall concordance was also high ( Although immunohistochemistry detects protein expression while RT-PCR measures mRNA transcription levels, numerous groups have shown a high degree of concordance between the two, particularly with regard to ER assessment.6,10,11,27,28 Concordance assessment of HR status examines protein and gene expression as dichotomous variables, as either positive or negative; however, equally important is whether HR biology is dichotomous or continuous.5,29 The LBA reported ER protein on a continuous scale with a large dynamic range. For IHC the Allred system was developed for semiquantitative ER assessment using a specific protocol and antibody and was superior to LBA.3 The Allred system semiquantifies both the percentage of positive cells and the intensity of staining: either 10% weakly staining nuclei or 1% intermediately staining nuclei represent the cut point for HR positivity. AS has been optimized for use with other protocols and antibodies, most recently in the validation of the FDA-approved ER/PR pharmDx Kit. For the semiquantitation of PR, Mohsin et al30 demonstrated the utility of the Allred system with similar success. However, implementation of the AS system in different laboratories may give results that differ from the specific methodology employed in the original Allred studies. As shown, the Oncotype DX RT-PCR measures of ER and PR exhibit a continuous distribution of expression over a 3,000-fold and 1,000-fold range, respectively, for ER and PR. In contrast, using the ER clone 1D5 and PR clone 636 AS tended to be bimodal.27 The relationship between recurrence risk and ER expression by central IHC and central RT-PCR was explored. Five-year recurrence rate estimates were obtained for all patients, and separately for the ER-positive patients who received chemohormonal therapy. As expected, ER by both central IHC and central RT-PCR were significantly associated with relapse when all patients were included in the analysis (P < .0001 for both). When the ER-positive subgroup was analyzed, ER expression by central IHC AS was marginally associated with recurrence (P = .091), while ER expression by central RT-PCR was significantly associated with recurrence (P = .014). The National Surgical Adjuvant Breast and Bowel Project (NSABP) B-14 Oncotype DX study in ER-positive patients treated with placebo or tamoxifen showed that quantitative ER was the best single predictor of tamoxifen benefit (interaction P = .0007).27 Possibly in this study, where all ER-positive patients received combined chemohormonal therapy, ER is less associated with recurrence risk because chemotherapy benefit was lower in patients with higher ER.31 In contrast, in this subgroup of ER-positive patients, the RS, which incorporates other biologic pathways beyond ER, was a highly significant predictor of recurrence (P < .0001). In summary, this study demonstrated a high level of concordance for ER, PR, and HR between local and central IHC laboratories and central RT-PCR using the Oncotype DX assay. Quantitative RT-PCR using the Oncotype DX assay is an alternative method for determining hormone receptor status.
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: Frederick L. Baehner, Genomic Health Inc (C); Barrett H Childs, Sanofi-aventis (C); Tara Maddala, Genomic Health Inc (C); Mei-Lan Liu, Genomic Health Inc (C); Steve C. Rowley, Sanofi-aventis (C); Steven Shak, Genomic Health Inc (C) Consultant or Advisory Role: Joseph A. Sparano, Genomic Health Inc (C) Stock Ownership: Frederick L. Baehner, Genomic Health Inc; Steven Shak, Genomic Health Inc Honoraria: None Research Funding: None Expert Testimony: None Other Remuneration: None
Conception and design: Sunil S. Badve, Robert P. Gray, Barrett H. Childs, Steve C. Rowley, Steven Shak, George W. Sledge, Lori J. Goldstein, Joseph A. Sparano Financial support: Barrett H. Childs, Steve C. Rowley Administrative support: Robert P. Gray, George W. Sledge Provision of study materials or patients: Robert P. Gray, Edith D. Perez, Lawrence J. Shulman, Silvana Martino, Nancy E. Davidson, George W. Sledge, Lori J. Goldstein Collection and assembly of data: Frederick L. Baehner, Robert P. Gray, Steven Shak, Joseph A. Sparano Data analysis and interpretation: Sunil S. Badve, Frederick L. Baehner, Robert P. Gray, Barrett H. Childs, Tara Maddala, Mei-Lan Liu, Steve C. Rowley, Steven Shak, Lori J. Goldstein, Joseph A. Sparano Manuscript writing: Sunil S. Badve, Frederick L. Baehner, Robert P. Gray, Barrett H. Childs, Tara Maddala, Mei-Lan Liu, Steve C. Rowley, Steven Shak, Nancy E. Davidson, George W. Sledge, Joseph A. Sparano Final approval of manuscript: Sunil S. Badve, Frederick L. Baehner, Robert P. Gray, Barrett H. Childs, Tara Maddala, Mei-Lan Liu, Steve C. Rowley, Steven Shak, Edith D. Perez, Lawrence J. Shulman, Silvana Martino, Nancy E. Davidson, George W. Sledge, Lori J. Goldstein, Joseph A. Sparano
We thank Adekunle Raji and other staff members at the Eastern Cooperative Oncology Group Pathology Coordinating Office at the Robert H. Lurie Comprehensive Cancer Center, Chicago, IL.
Supported by Genomic Health Inc and sanofi-aventis. Terms in blue are defined in the glossary, found at the end of this article and online at www.jco.org. Authors’ disclosures of potential conflicts of interest and author contributions are found at the end of this article.
1. McGuire WL, Carbone P, Sears M: Estrogen Receptors in Human Breast Cancer: An Overview. New York, NY, Raven Press, 1975 2. Rhodes A, Jasani B, Balaton AJ, et al: Study of interlaboratory reliability and reproducibility of estrogen and progesterone receptor assays in Europe: Documentation of poor reliability and identification of insufficient microwave antigen retrieval time as a major contributory element of unreliable assays. Am J Clin Pathol 115:44-58, 2001[CrossRef][Medline] 3. Harvey JM, Clark GM, Osborne CK, et al: Estrogen receptor status by immunohistochemistry is superior to the ligand-binding assay for predicting response to adjuvant endocrine therapy in breast cancer. J Clin Oncol 17:1474-1481, 1999 4. Rhodes A, Jasani B, Balaton AJ, et al: Immunohistochemical demonstration of oestrogen and progesterone receptors: Correlation of standards achieved on in house tumours with that achieved on external quality assessment material in over 150 laboratories from 26 countries. J Clin Pathol 53:292-301, 2000 5. Collins LC, Botero ML, Schnitt SJ: Bimodal frequency distribution of estrogen receptor immunohistochemical staining results in breast cancer: An analysis of 825 cases. Am J Clin Pathol 123:16-20, 2005[CrossRef][Medline] 6. Cronin M, Pho M, Dutta D, et al: Measurement of gene expression in archival paraffin-embedded tissues: Development and performance of a 92-gene reverse transcriptase-polymerase chain reaction assay. Am J Pathol 164:35-42, 2004 7. Goldstein NS, Ferkowicz M, Odish E, et al: Minimum formalin fixation time for consistent estrogen receptor immunohistochemical staining of invasive breast carcinoma. Am J Clin Pathol 120:86-92, 2003[CrossRef][Medline] 8. Kononen J, Bubendorf L, Kallioniemi A, et al: Tissue microarrays for high-throughput molecular profiling of tumor specimens. Nat Med 4:844-847, 1998[CrossRef][Medline] 9. Paik S, Shak S, Tang G, et al: A multigene assay to predict recurrence of tamoxifen-treated, node-negative breast cancer. N Engl J Med 351:2817-2826, 2004 10. Esteva FJ, Sahin AA, Cristofanilli M, et al: Prognostic role of a multigene reverse transcriptase-PCR assay in patients with node-negative breast cancer not receiving adjuvant systemic therapy. Clin Cancer Res 11:3315-3319, 2005 11. Mina L, Soule SE, Badve S, et al: Predicting response to primary chemotherapy: Gene expression profiling of paraffin-embedded core biopsy tissue. Breast Cancer Res Treat 103:197-208, 2007[CrossRef][Medline] 12. Prentice RL: On the design of synthetic case-control studies. Biometrics 42:301-310, 1986[CrossRef][Medline] 13. Cohen J: A coefficient of agreement for nominal scales. Educ Psychol Measure 20:27-46, 1960 14. Collett D: Modeling Binary Data. London, United Kingdom, Chapman and Hall, 1991 15. Chen K, Lo SH: Case-cohort and case-control analysis with Cox's model. Biometrika 86:755-764, 1999 16. Guidance for Industry and FDA Staff: Statistical Guidance on Reporting Results from Studies Evaluating Diagnostic Tests. Rockville, MD, Center for Devices and Radiological Health, 2007 17. Knight WA, Livingston RB, Gregory EJ, et al: Estrogen receptor as an independent prognostic factor for early recurrence in breast cancer. Cancer Res 37:4669-4671, 1977 18. Effects of chemotherapy and hormonal therapy for early breast cancer on recurrence and 15-year survival: An overview of the randomised trials. Lancet 365:1687-1717, 2005[CrossRef][Medline] 19. Bast RC Jr, Ravdin P, Hayes DF, et al: 2000 Update of recommendations for the use of tumor markers in breast and colorectal cancer: Clinical practice guidelines of the American Society of Clinical Oncology. J Clin Oncol 19:1865-1878, 2001 20. Rhodes A, Jasani B, Barnes DM, et al: Reliability of immunohistochemical demonstration of oestrogen receptors in routine practice: Interlaboratory variance in the sensitivity of detection and evaluation of scoring systems. J Clin Pathol 53:125-130, 2000 21. Wolff AC, Hammond ME, Schwartz JN, et al: American Society of Clinical Oncology/College of American Pathologists guideline recommendations for human epidermal growth factor receptor 2 testing in breast cancer. J Clin Oncol 25:118-145, 2007 22. Vandesompele J, De Preter K, Pattyn F, et al: Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes. Genome Biol 3:RESEARCH0034, 2002 23. Suzuki T, Higgins PJ, Crawford DR: Control selection for RNA quantitation. Biotechniques 29:332-337, 2000[Medline] 24. Ming Z, Bronner M, Magi-Galluzzi C, et al: Optimized RNA extraction and RT-PCR assays provide successful molecular analysis on a wide variety of archival fixed tissues. Presented at the Annual Meeting of the American Association for Cancer Research April 14-17, 2007, Los Angeles, CA 25. Cronin M, Sangli C, Liu ML, et al: Analytical validation of the Oncotype DX genomic diagnostic test for recurrence prognosis and therapeutic response prediction in node-negative, estrogen receptor-positive breast cancer. Clin Chem 53:1084-1091, 2007 26. Shak S, Baehner FL, Palmer G, et al: Subtypes of breast cancer defined by standardized quantitative RT-PCR analysis of 10,618 tumors: Updated analysis with 20,050 tumors. Presented at the 29th Annual San Antonio Breast Cancer Symposium, December 14-17, 2006, San Antonio, TX 27. Baehner FL, Habel LA, Quesenberry CP, et al: Quantitative RT-PCR analysis of ER and PR by Oncotype DX indicates distinct and different associations with prognosis and prediction of tamoxifen benefit. Presented at the 29th Annual San Antonio Breast Cancer Symposium, December 14-17, 2006, San Antonio, TX 28. Ma XJ, Hilsenbeck SG, Wang W, et al: The HOXB13:IL17BR expression index is a prognostic factor in early-stage breast cancer. J Clin Oncol 24:4611-4619, 2006 29. Nadji M, Gomez-Fernandez C, Ganjei-Azar P, et al: Immunohistochemistry of estrogen and progesterone receptors reconsidered: Experience with 5,993 breast cancers. Am J Clin Pathol 123:21-27, 2005[CrossRef][Medline] 30. Mohsin SK, Weiss H, Havighurst T, et al: Progesterone receptor by immunohistochemistry and clinical outcome in breast cancer: A validation study. Mod Pathol 17:1545-1554, 2004[CrossRef][Medline] 31. Goldstein LJ, O'Neill A, Sparano J, et al: E2197 Phase III AT (doxorubicin/docetaxel) vs AC (doxorubicin/cyclophosphamide) in the adjuvant treatment off node positive and high risk node negative breast cancer. J Clin Oncol 23:7s, 2005 (abstr 512) Submitted August 12, 2007; accepted February 21, 2008. This article has been cited by other articles:
|
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
|
|
|||||||||||
|
|||||||||||
|
|
Copyright © 2008 by the American Society of Clinical Oncology, Online ISSN: 1527-7755. Print ISSN: 0732-183X
|
TOP
ABSTRACT
INTRODUCTION
) Calculated using a Cox proportional hazards model including only positive ER values (n = 409 for IHC and n = 459 for RT-PCR); (B) (*) Calculated using a Cox proportional hazards model including all ER values (n = 723 for IHC and n=714 for RT-PCR); (
90%); nevertheless, between 8% (central IHC) and 12% (local IHC) of samples classified as HR negative by IHC were HR positive by RT-PCR. 
