Decision impact and feasibility of different ASCO-recommended biomarkers in early breast cancer: Prospective comparison of molecular marker EndoPredict and protein marker uPA/PAI-1.

BACKGROUND: Adjuvant therapy decisions in early breast cancer are based on accurate risk assessment. Urokinase plasminogen activator (uPA) and plaminogen activator inhibitor-1 (PAI-1) have been the first biomarkers in hormone receptor (HR) positive breast cancer to reach highest level of evidence. The EndoPredict test (EPclin) combines gene expression information with nodal status and tumor size. The aim of this prospective study was to compare uPA/PAI-1 and EPclin as prognostic biomarkers with regard to feasibility, risk stratification and impact on adjuvant therapy recommendation. MATERIALS AND METHOD: 395 patients with HR positive, HER2 negative, intermediate risk breast cancer were enrolled. Relations and concordance of histologic grading as well as EPclin and uPA/PAI-1 values were assessed by Spearman's rank correlation coefficient and Cohen's Kappa. To compare decision impact of EPclin and uPA/PAI-1 three independent case discussions were held: One with known uPA/PAI-1 and EPclin results, one blinded to EPclin alone and another one blinded to both EPclin and uPA/PAI-1. RESULTS: EPclin could be determined in all 395 (100%), uPA/PAI-1 in 190 (48%) of the tumor samples. EPclin allocated 250 patients (63%) to the low-risk group and 145 patients (37%) to the high-risk group, whereas uPA/PAI-1 allocated 88 patients (46%) to the low-risk group and 102 patients (54%) to the high-risk group. In 59% of cases, both tests showed concordant results. EPclin resulted more frequently in a change of therapy recommendation than the uPA/PAI-1 test (46% vs 24%). Recommendation of adjuvant chemotherapy (CTX) was abandoned twice as often by EPclin (45%) compared to uPA/PAI-1 (22%). CONCLUSION: In this first prospective comparison of EPclin and uPA/PAI-1 we found, that EPclin is superior to uPA/PAI-1 with respect to feasibility and decision impact. This leads to substantial avoidance of adjuvant CTX in endocrine-sensitive, HER2-negative breast cancer. Data collection for patients´ clinical outcome is ongoing.

Comparison of EndoPredict and EPclin With Oncotype DX Recurrence Score for Prediction of Risk of Distant Recurrence After Endocrine Therapy.

BACKGROUND: Estimating distant recurrence (DR) risk among women with estrogen receptor-positive (ER+), human epidermal growth factor receptor 2 (HER2)-negative early breast cancer helps decisions on using adjuvant chemotherapy. The 21-gene Oncotype DX recurrence score (RS) is widely used for this. EndoPredict (EPclin) is an alternative test combining prognostic information from an eight-gene signature (EP score) with tumor size and nodal status. We compared the prognostic information provided by RS and EPclin for 10-year DR risk. METHODS: We used likelihood ratio χ² and Kaplan-Meier survival analyses to compare prognostic information provided by EP, EPclin, RS, and the clinical treatment score (CTS) of clinicopathologic parameters in 928 patients with ER+ disease treated with five years' anastrozole or tamoxifen. Comparisons were made for early (0-5 years) and late (5-10 years) DR according to nodal status. All statistical tests were two-sided. RESULTS: In the overall population, EP and EPclin provided substantially more prognostic information than RS (LRχ(2): EP = 49.3; LRχ(2): EPclin = 139.3; LRχ(2): RS = 29.1), with greater differences in late DR and in node-positive patients. EP and EPclin remained statistically significantly prognostic when adjusted for RS (ΔLRχ(2): EP+RS vs RS = 20.2; ΔLRχ(2): EPclin+RS vs RS = 113.8). Using predefined cut-offs, EPclin and RS identified 58.8% and 61.7% patients as low risk, with hazard ratios for non-low vs low risk of 5.99 (95% confidence interval [CI] = 3.94 to 9.11) and 2.73 (95% CI = 1.91 to 3.89), respectively. CONCLUSIONS: EP and EPclin were highly prognostic for DR in endocrine-treated patients with ER+, HER2-negative disease. EPclin provided more prognostic information than RS. This was partly but not entirely because of EPclin integrating molecular data with nodal status and tumor size.

Prognostic ability of EndoPredict compared to research-based versions of the PAM50 risk of recurrence (ROR) scores in node-positive, estrogen receptor-positive, and HER2-negative breast cancer. A GEICAM/9906 sub-study.

There are several prognostic multigene-based tests for managing breast cancer (BC), but limited data comparing them in the same cohort. We compared the prognostic performance of the EndoPredict (EP) test (standardized for pathology laboratory) with the research-based PAM50 non-standardized qRT-PCR assay in node-positive estrogen receptor-positive (ER+) and HER2-negative (HER2-) BC patients receiving adjuvant chemotherapy followed by endocrine therapy (ET) in the GEICAM/9906 trial. EP and PAM50 risk of recurrence (ROR) scores [based on subtype (ROR-S) and on subtype and proliferation (ROR-P)] were compared in 536 ER+/HER2- patients. Scores combined with clinical information were evaluated: ROR-T (ROR-S, tumor size), ROR-PT (ROR-P, tumor size), and EPclin (EP, tumor size, nodal status). Patients were assigned to risk-categories according to prespecified cutoffs. Distant metastasis-free survival (MFS) was analyzed by Kaplan-Meier. ROR-S, ROR-P, and EP scores identified a low-risk group with a relative better outcome (10-year MFS: ROR-S 87 %; ROR-P 89 %; EP 93 %). There was no significant difference between tests. Predictors including clinical information showed superior prognostic performance compared to molecular scores alone (10-year MFS, low-risk group: ROR-T 88 %; ROR-PT 92 %; EPclin 100 %). The EPclin-based risk stratification achieved a significantly improved prediction of MFS compared to ROR-T, but not ROR-PT. All signatures added prognostic information to common clinical parameters. EPclin provided independent prognostic information beyond ROR-T and ROR-PT. ROR and EP can reliably predict risk of distant metastasis in node-positive ER+/HER2- BC patients treated with chemotherapy and ET. Addition of clinical parameters into risk scores improves their prognostic ability.

Clinical validation of the EndoPredict test in node-positive, chemotherapy-treated ER+/HER2- breast cancer patients: results from the GEICAM 9906 trial.

INTRODUCTION: EndoPredict (EP) is an RNA-based multigene test that predicts the likelihood of distant recurrence in patients with estrogen receptor-positive (ER+), human epidermal growth factor receptor 2-negative (HER2-) breast cancer (BC) who are being treated with adjuvant endocrine therapy. Herein we report the prospective-retrospective clinical validation of EP in the node-positive, chemotherapy-treated, ER+/HER2- BC patients in the GEICAM 9906 trial. METHODS: The patients (N = 1,246) were treated either with six cycles of fluorouracil, epirubicin and cyclophosphamide (FEC) or with four cycles of FEC followed by eight weekly courses of paclitaxel (FEC-P), as well as with endocrine therapy if they had hormone receptor-positive disease. The patients were assigned to EP risk categories (low or high) according to prespecified cutoff levels. The primary endpoint in the clinical validation of EP was distant metastasis-free survival (MFS). Metastasis rates were estimated using the Kaplan-Meier method, and multivariate analysis was performed using Cox regression. RESULTS: The molecular EP score and the combined molecular and clinical EPclin score were successfully determined in 555 ER+/HER2- tumors from the 800 available samples in the GEICAM 9906 trial. On the basis of the EP, 25% of patients (n = 141) were classified as low risk. MFS was 93% in the low-risk group and 70% in the high-risk group (absolute risk reduction = 23%, hazard ratio (HR) = 4.8, 95% confidence interval (CI) = 2.5 to 9.5; P < 0.0001). Multivariate analysis showed that, in this ER+/HER2- cohort, EP results are an independent prognostic parameter after adjustment for age, grade, lymph node status, tumor size, treatment arm, ER and progesterone receptor (PR) status and proliferation index (Ki67). Using the predefined EPclin score, 13% of patients (n = 74) were assigned to the low-risk group, who had excellent outcomes and no distant recurrence events (absolute risk reduction vs high-risk group = 28%; P < 0.0001). Furthermore, EP was prognostic in premenopausal patients (HR = 6.7, 95% CI = 2.4 to 18.3; P = 0.0002) and postmenopausal patients (HR = 3.3, 95% CI = 1.3 to 8.5; P = 0.0109). There were no statistically significant differences in MFS between treatment arms (FEC vs FEC-P) in either the high- or low-risk groups. The interaction test results between the chemotherapy arm and the EP score were not significant. CONCLUSIONS: EP is an independent prognostic parameter in node-positive, ER+/HER2- BC patients treated with adjuvant chemotherapy followed by hormone therapy. EP did not predict a greater efficacy of FEC-P compared to FEC alone.

From High-Throughput Microarray-Based Screening to Clinical Application: The Development of a Second Generation Multigene Test for Breast Cancer Prognosis.

Several multigene tests have been developed for breast cancer patients to predict the individual risk of recurrence. Most of the first generation tests rely on proliferation-associated genes and are commonly carried out in central reference laboratories. Here, we describe the development of a second generation multigene assay, the EndoPredict test, a prognostic multigene expression test for estrogen receptor (ER) positive, human epidermal growth factor receptor (HER2) negative (ER+/HER2-) breast cancer patients. The EndoPredict gene signature was initially established in a large high-throughput microarray-based screening study. The key steps for biomarker identification are discussed in detail, in comparison to the establishment of other multigene signatures. After biomarker selection, genes and algorithms were transferred to a diagnostic platform (reverse transcription quantitative PCR (RT-qPCR)) to allow for assaying formalin-fixed, paraffin-embedded (FFPE) samples. A comprehensive analytical validation was performed and a prospective proficiency testing study with seven pathological laboratories finally proved that EndoPredict can be reliably used in the decentralized setting. Three independent large clinical validation studies (n = 2,257) demonstrated that EndoPredict offers independent prognostic information beyond current clinicopathological parameters and clinical guidelines. The review article summarizes several important steps that should be considered for the development process of a second generation multigene test and offers a means for transferring a microarray signature from the research laboratory to clinical practice.

Gene-expression signature of tumor recurrence in patients with stage II and III colon cancer treated with 5'fluoruracil-based adjuvant chemotherapy.

Although receiving adjuvant chemotherapy after radical surgery, a disappointing proportion of patients with colorectal cancer will develop tumor recurrence. Probability of relapse is currently predicted from pathological staging, there being a need for additional markers to further select high-risk patients. This study was aimed to identify a gene-expression signature to predict tumor recurrence in patients with Stages II and III colon cancer treated with 5'fluoruracil (5FU)-based adjuvant chemotherapy. Two-hundred and twenty-eight patients diagnosed with Stages II-III colon cancer and treated with surgical resection and 5FU-based adjuvant chemotherapy were included. RNA was extracted from formalin-fixed, paraffin-embedded tissue samples and expression of 27 selected candidate genes was analyzed by RT-qPCR. A tumor recurrence predicting model, including clinico-pathological variables and gene-expression profiling, was developed by Cox regression analysis and validated by bootstrapping. The regression analysis identified tumor stage and S100A2 and S100A10 gene expression as independently associated with tumor recurrence. The risk score derived from this model was able to discriminate two groups with a highly significant different probability of tumor recurrence (HR, 2.75; 95%CI, 1.71-4.39; p = 0.0001), which it was maintained when patients were stratified according to tumor stage. The algorithm was also able to distinguish two groups with different overall survival (HR, 2.68; 95%CI, 1.12-6.42; p = 0.03). Identification of a new gene-expression signature associated with a high probability of tumor recurrence in patients with Stages II and III colon cancer receiving adjuvant 5FU-based chemotherapy, and its combination in a robust, easy-to-use and reliable algorithm may contribute to tailor treatment and surveillance strategies.

Decentral gene expression analysis: analytical validation of the Endopredict genomic multianalyte breast cancer prognosis test.

BACKGROUND: EndoPredict (EP) is a clinically validated multianalyte gene expression test to predict distant metastasis in ER-positive, HER2-negative breast cancer treated with endocrine therapy alone. The test is based on the combined analysis of 12 genes in formalin-fixed, paraffin-embedded (FFPE) tissue by reverse transcription-quantitative real-time PCR (RT-qPCR). Recently, it was shown that EP is feasible for reliable decentralized assessment of gene expression. The aim of this study was the analytical validation of the performance characteristics of the assay and its verification in a molecular-pathological routine laboratory. METHODS: Gene expression values to calculate the EP score were assayed by one-step RT-qPCR using RNA from FFPE tumor tissue. Limit of blank, limit of detection, linear range, and PCR efficiency were assessed for each of the 12 PCR assays using serial samples dilutions. Different breast cancer samples were used to evaluate RNA input range, precision and inter-laboratory variability. RESULTS: PCR assays were linear up to Cq values between 35.1 and 37.2. Amplification efficiencies ranged from 75% to 101%. The RNA input range without considerable change of the EP score was between 0.16 and 18.5 ng/µl. Analysis of precision (variation of day, day time, instrument, operator, reagent lots) resulted in a total noise (standard deviation) of 0.16 EP score units on a scale from 0 to 15. The major part of the total noise (SD 0.14) was caused by the replicate-to-replicate noise of the PCR assays (repeatability) and was not associated with different operating conditions (reproducibility). Performance characteristics established in the manufacturer's laboratory were verified in a routine molecular pathology laboratory. Comparison of 10 tumor samples analyzed in two different laboratories showed a Pearson coefficient of 0.995 and a mean deviation of 0.15 score units. CONCLUSIONS: The EP test showed reproducible performance characteristics with good precision and negligible laboratory-to-laboratory variation. This study provides further evidence that the EP test is suitable for decentralized testing in specialized molecular pathological laboratories instead of a reference laboratory. This is a unique feature and a technical advance in comparison with existing RNA-based prognostic multigene expression tests.

Comparison of the RNA-based EndoPredict multigene test between core biopsies and corresponding surgical breast cancer sections.

AIM: This study compared the perfomance of the RNA-based EndoPredict multigene test on core biopsies and surgical breast cancer specimens and analysed the influence of biopsy-induced tissue injuries on the test result. METHODS: 80 formalin-fixed paraffin-embedded samples comprising paired biopsies and surgical specimens from 40 ER-positive, HER2-negative patients were evaluated. Total RNA was extracted and the EndoPredict score was determined. RESULTS: RNA yield was considerably lower in core biopsies, but sufficient to measure the assay in all samples. The EndoPredict score was highly correlated between paired samples (Pearson r=0.92), with an excellent concordance of classification into a low or high risk of metastasis (overall agreement 95%). CONCLUSIONS: The measurements are comparable between core biopsies and surgical sections, which suggest that the EndoPredict assay can be performed on core biopsy tissue. Inflammatory changes induced by presurgical biopsies had no significant effect on the RNA-based risk assessment in surgical specimens.

Decentral gene expression analysis for ER+/Her2- breast cancer: results of a proficiency testing program for the EndoPredict assay.

Gene expression profiles provide important information about the biology of breast tumors and can be used to develop prognostic tests. However, the implementation of quantitative RNA-based testing in routine molecular pathology has not been accomplished, so far. The EndoPredict assay has recently been described as a quantitative RT-PCR-based multigene expression test to identify a subgroup of hormone-receptor-positive tumors that have an excellent prognosis with endocrine therapy only. To transfer this test from bench to bedside, it is essential to evaluate the test-performance in a multicenter setting in different molecular pathology laboratories. In this study, we have evaluated the EndoPredict (EP) assay in seven different molecular pathology laboratories in Germany, Austria, and Switzerland. A set of ten formalin-fixed paraffin-embedded tumors was tested in the different labs, and the variance and accuracy of the EndoPredict assays were determined using predefined reference values. Extraction of a sufficient amount of RNA and generation of a valid EP score was possible for all 70 study samples (100%). The EP scores measured by the individual participants showed an excellent correlation with the reference values, respectively, as reflected by Pearson correlation coefficients ranging from 0.987 to 0.999. The Pearson correlation coefficient of all values compared to the reference value was 0.994. All laboratories determined EP scores for all samples differing not more than 1.0 score units from the pre-defined references. All samples were assigned to the correct EP risk group, resulting in a sensitivity and specificity of 100%, a concordance of 100%, and a kappa of 1.0. Taken together, the EndoPredict test could be successfully implemented in all seven participating laboratories and is feasible for reliable decentralized assessment of gene expression in luminal breast cancer.

Quantitative determination of estrogen receptor, progesterone receptor, and HER2 mRNA in formalin-fixed paraffin-embedded tissue--a new option for predictive biomarker assessment in breast cancer.

The development of optimized therapy strategies against malignant tumors is critically dependent on the assessment of tissue-based biomarkers in routine diagnostic tissue samples. We investigated a novel, fully automated, and xylene-free method for RNA isolation and biomarker determination using formalin-fixed paraffin-embedded (FFPE) tissue. The aim was to show that this approach is feasible and gives results that are comparable to the current gold standards. Expression of the breast cancer biomarkers ESR1, PGR, and HER2 was measured in a total of 501 FFPE tissue samples from 167 breast carcinomas, which had been stored for up to 21 years. Total RNA was extracted from tissue sections and biomarker expression was measured by kinetic RT-PCR (RT-kPCR). The results of the new method were compared with immunohistochemistry as the current gold standard.RNA was successfully isolated from all samples, with a mean yield of 1.4 µg/sample and fragment lengths of at least 150 bp in 99% of samples. RT-kPCR analysis of ESR1, PGR, and HER2 was possible in all samples. Comparing RT-kPCR results with standard IHC, we found a good concordance for ESR1 (agreement: 98.4%), PGR (84.4%), and HER2 (89.8%). We observed a low section-to-section variability of kPCR results for all 3 biomarkers (root of mean squared errors: 0.2 to 0.5 Ct values). The new approach is a reliable high-throughput instrument for standardized testing of biomarkers in clinical routine and for research studies on archived FFPE material up to 21 years old. For the assessment of ESR1, PGR, and HER2 the results are comparable to the current gold-standard.