Aromatase inhibition plus/minus Src inhibitor saracatinib (AZD0530) in advanced breast cancer therapy (ARISTACAT): a randomised phase II study.

PURPOSE: The development of oestrogen resistance is a major challenge in managing hormone-sensitive metastatic breast cancer. Saracatinib (AZD0530), an oral Src kinase inhibitor, prevents oestrogen resistance in animal models and reduces osteoclast activity. We aimed to evaluate the efficacy of saracatinib addition to aromatase inhibitors (AI) in patients with hormone receptor-positive metastatic breast cancer. METHODS: This phase II multicentre double-blinded randomised trial allocated post-menopausal women to AI with either saracatinib or placebo (1:1 ratio). Patients were stratified into an "AI-sensitive/naïve" group who received anastrozole and "prior-AI" group who received exemestane. Primary endpoint was progression-free survival (PFS). Secondary endpoints included overall survival (OS), objective response rate (ORR) and toxicity. RESULTS: 140 patients were randomised from 20 UK centres to saracatinib/AI (n = 69) or placebo/AI (n = 71). Saracatinib was not associated with an improved PFS (3.7 months v. 5.6 months placebo/AI) and did not reduce likelihood of bony progression. There was no benefit in OS or ORR. Effects were consistent in "AI-sensitive/naive" and "prior-AI" sub-groups. Saracatinib was well tolerated with dose reductions in 16% and the main side effects were gastrointestinal, hypophosphatemia and rash. CONCLUSION: Saracatinib did not improve outcomes in post-menopausal women with metastatic breast cancer. There was no observed beneficial effect on bone metastases. CRUKE/11/023, ISRCTN23804370.

Correlative studies of the Breast Cancer Index (HOXB13/IL17BR) and ER, PR, AR, AR/ER ratio and Ki67 for prediction of extended endocrine therapy benefit: a Trans-aTTom study.

BACKGROUND: Multiple clinical trials demonstrate consistent but modest benefit of adjuvant extended endocrine therapy (EET) in HR + breast cancer patients. Predictive biomarkers to identify patients that benefit from EET are critical to balance modest reductions in risk against potential side effects of EET. This study compares the performance of the Breast Cancer Index, BCI (HOXB13/IL17BR, H/I), with expression of estrogen (ER), progesterone (PR), and androgen receptors (AR), and Ki67, for prediction of EET benefit. METHODS: Node-positive (N+) patients from the Trans-aTTom study with available tissue specimen and BCI results (N = 789) were included. Expression of ER, PR, AR, and Ki67 was assessed by quantitative immunohistochemistry. BCI (H/I) gene expression analysis was conducted by quantitative RT-PCR. Statistical significance of the treatment by biomarker interaction was evaluated by likelihood ratio tests based on multivariate Cox proportional models, adjusting for age, tumor size, grade, and HER2 status. Pearson's correlation coefficients were calculated to evaluate correlations between BCI (H/I) versus ER, PR, AR, Ki67 and AR/ER ratio. RESULTS: EET benefit, measured by the difference in risk of recurrence between patients treated with tamoxifen for 10 versus 5 years, is significantly associated with increasing values of BCI (H/I) (interaction P = 0.01). In contrast, expression of ER (P = 0.83), PR (P = 0.66), AR (P = 0.78), Ki67 (P = 0.87) and AR/ER ratio (P = 0.84) exhibited no significant relationship with EET benefit. BCI (H/I) showed a very weak negative correlation with ER (r = - 0.18), PR (r = - 0.25), and AR (r = - 0.14) expression, but no correlation with either Ki67 (r = 0.04) or AR/ER ratio (r = 0.02). CONCLUSION: These findings are consistent with the growing body of evidence that BCI (H/I) is significantly predictive of response to EET and outcome. Results from this direct comparison demonstrate that expression of ER, PR, AR, Ki67 or AR/ER ratio are not predictive of benefit from EET. BCI (H/I) is the only clinically validated biomarker that predicts EET benefit.

Systematically higher Ki67 scores on core biopsy samples compared to corresponding resection specimen in breast cancer: a multi-operator and multi-institutional study.

Ki67 has potential clinical importance in breast cancer but has yet to see broad acceptance due to inter-laboratory variability. Here we tested an open source and calibrated automated digital image analysis (DIA) platform to: (i) investigate the comparability of Ki67 measurement across corresponding core biopsy and resection specimen cases, and (ii) assess section to section differences in Ki67 scoring. Two sets of 60 previously stained slides containing 30 core-cut biopsy and 30 corresponding resection specimens from 30 estrogen receptor-positive breast cancer patients were sent to 17 participating labs for automated assessment of average Ki67 expression. The blocks were centrally cut and immunohistochemically (IHC) stained for Ki67 (MIB-1 antibody). The QuPath platform was used to evaluate tumoral Ki67 expression. Calibration of the DIA method was performed as in published studies. A guideline for building an automated Ki67 scoring algorithm was sent to participating labs. Very high correlation and no systematic error (p = 0.08) was found between consecutive Ki67 IHC sections. Ki67 scores were higher for core biopsy slides compared to paired whole sections from resections (p ≤ 0.001; median difference: 5.31%). The systematic discrepancy between core biopsy and corresponding whole sections was likely due to pre-analytical factors (tissue handling, fixation). Therefore, Ki67 IHC should be tested on core biopsy samples to best reflect the biological status of the tumor.

Discordance between Immunohistochemistry and Erb-B2 Receptor Tyrosine Kinase 2 mRNA to Determine Human Epidermal Growth Factor Receptor 2 Low Status for Breast Cancer.

Novel human epidermal growth factor receptor 2 (HER2)-directed antibody-drug conjugates have demonstrated efficacy in HER2-low expressing breast cancers, which are currently defined as those with immunohistochemistry (IHC) scores of 1+ or 2+ with a negative in situ hybridization assay. However, current HER2 testing methods are designed to identify HER2-amplified tumors with high expression levels. The true definition of HER2-low expressing breast cancers remains controversial. Using quantitative molecular analysis of breast cancers based on RNA expression, the dynamic range of HER2 expression exceeds that detected by in situ IHC approaches. Erb-B2 receptor tyrosine kinase 2 (ERBB2) mRNA expression levels across IHC groups using patient samples derived from the Tamoxifen Exemestane Adjuvant Multicenter Trial were investigated. The standardized mean differences in ERBB2 mRNA scores in log base 2 are 0.47 (95% CI, 0.36-0.57), 0.58 (95% CI, 0.26-0.70), and 0.32 (95% CI, -0.12 to 0.75) when comparing IHC 0+ without staining versus IHC 0+ with some staining, IHC 0+ with some staining versus IHC 1+, and IHC 1+ versus IHC 2+/fluorescence in situ hybridization-negative, respectively. The results showed immunohistochemical methods have a comparatively limited dynamic range for measuring HER2 protein expression. The range of expression based on RNA abundance suggests a molecular method defining HER2-low cancers may better serve the treatment decision needs of this group. Indeed, the validity of RNA abundance to identify HER2-low cancers and predict treatment response needs to be further evaluated by prospective clinical trials.

Breast Cancer Index Is a Predictive Biomarker of Treatment Benefit and Outcome from Extended Tamoxifen Therapy: Final Analysis of the Trans-aTTom Study.

PURPOSE: The Breast Cancer Index (BCI) HOXB13/IL17BR (H/I) ratio predicts benefit from extended endocrine therapy in hormone receptor-positive (HR+) early-stage breast cancer. Here, we report the final analysis of the Trans-aTTom study examining BCI (H/I)'s predictive performance. EXPERIMENTAL DESIGN: BCI results were available for 2,445 aTTom trial patients. The primary endpoint of recurrence-free interval (RFI) and secondary endpoints of disease-free interval (DFI) and disease-free survival (DFS) were examined using Cox proportional hazards regression and log-rank test. RESULTS: Final analysis of the overall study population (N = 2,445) did not show a significant improvement in RFI with extended tamoxifen [HR, 0.90; 95% confidence interval (CI), 0.69-1.16; P = 0.401]. Both the overall study population and N0 group were underpowered due to the low event rate in the N0 group. In a pre-planned analysis of the N+ subset (N = 789), BCI (H/I)-High patients derived significant benefit from extended tamoxifen (9.7% absolute benefit: HR, 0.33; 95% CI, 0.14-0.75; P = 0.016), whereas BCI (H/I)-Low patients did not (-1.2% absolute benefit; HR, 1.11; 95% CI, 0.76-1.64; P = 0.581). A significant treatment-to-biomarker interaction was demonstrated on the basis of RFI, DFI, and DFS (P = 0.037, 0.040, and 0.025, respectively). BCI (H/I)-High patients remained predictive of benefit from extended tamoxifen in the N+/HER2- subgroup (9.4% absolute benefit: HR, 0.35; 95% CI, 0.15-0.81; P = 0.047). A three-way interaction evaluating BCI (H/I), treatment, and HER2 status was not statistically significant (P = 0.849). CONCLUSIONS: Novel findings demonstrate that BCI (H/I) significantly predicts benefit from extended tamoxifen in HR+ N+ patients with HER2- disease. Moreover, BCI (H/I) demonstrates significant treatment to biomarker interaction across survival outcomes.

Comparative survival analysis of multiparametric tests-when molecular tests disagree-A TEAM Pathology study.

Multiparametric assays for risk stratification are widely used in the management of both node negative and node positive hormone receptor positive invasive breast cancer. Recent data from multiple sources suggests that different tests may provide different risk estimates at the individual patient level. The TEAM pathology study consists of 3284 postmenopausal ER+ve breast cancers treated with endocrine therapy Using genes comprising the following multi-parametric tests OncotypeDx®, Prosigna™ and MammaPrint® signatures were trained to recapitulate true assay results. Patients were then classified into risk groups and survival assessed. Whilst likelihood χ2 ratios suggested limited value for combining tests, Kaplan-Meier and LogRank tests within risk groups suggested combinations of tests provided statistically significant stratification of potential clinical value. Paradoxically whilst Prosigna-trained results stratified Oncotype-trained subgroups across low and intermediate risk categories, only intermediate risk Prosigna-trained cases were further stratified by Oncotype-trained results. Both Oncotype-trained and Prosigna-trained results further stratified MammaPrint-trained low risk cases, and MammaPrint-trained results also stratified Oncotype-trained low and intermediate risk groups but not Prosigna-trained results. Comparisons between existing multiparametric tests are challenging, and evidence on discordance between tests in risk stratification presents further dilemmas. Detailed analysis of the TEAM pathology study suggests a complex inter-relationship between test results in the same patient cohorts which requires careful evaluation regarding test utility. Further prognostic improvement appears both desirable and achievable.

Evaluation of multiple transcriptomic gene risk signatures in male breast cancer.

Male breast cancer (BCa) is a rare disease accounting for less than 1% of all breast cancers and 1% of all cancers in males. The clinical management is largely extrapolated from female BCa. Several multigene assays are increasingly used to guide clinical treatment decisions in female BCa, however, there are limited data on the utility of these tests in male BCa. Here we present the gene expression results of 381 M0, ER+ve, HER2-ve male BCa patients enrolled in the Part 1 (retrospective analysis) of the International Male Breast Cancer Program. Using a custom NanoString™ panel comprised of the genes from the commercial risk tests Prosigna®, OncotypeDX®, and MammaPrint®, risk scores and intrinsic subtyping data were generated to recapitulate the commercial tests as described by us previously. We also examined the prognostic value of other risk scores such as the Genomic Grade Index (GGI), IHC4-mRNA and our prognostic 95-gene signature. In this sample set of male BCa, we demonstrated prognostic utility on univariate analysis. Across all signatures, patients whose samples were identified as low-risk experienced better outcomes than intermediate-risk, with those classed as high risk experiencing the poorest outcomes. As seen with female BCa, the concordance between tests was poor, with C-index values ranging from 40.3% to 78.2% and Kappa values ranging from 0.17 to 0.58. To our knowledge, this is the largest study of male breast cancers assayed to generate risk scores of the current commercial and academic risk tests demonstrating comparable clinical utility to female BCa.

Computational approaches to support comparative analysis of multiparametric tests: Modelling versus Training.

Multiparametric assays for risk stratification are widely used in the management of breast cancer, with applications being developed for a number of other cancer settings. Recent data from multiple sources suggests that different tests may provide different risk estimates at the individual patient level. There is an increasing need for robust methods to support cost effective comparisons of test performance in multiple settings. The derivation of similar risk classifications using genes comprising the following multi-parametric tests Oncotype DX® (Genomic Health.), Prosigna™ (NanoString Technologies, Inc.), MammaPrint® (Agendia Inc.) was performed using different computational approaches. Results were compared to the actual test results. Two widely used approaches were applied, firstly computational "modelling" of test results using published algorithms and secondly a "training" approach which used reference results from the commercially supplied tests. We demonstrate the potential for errors to arise when using a "modelling" approach without reference to real world test results. Simultaneously we show that a "training" approach can provide a highly cost-effective solution to the development of real-world comparisons between different multigene signatures. Comparisons between existing multiparametric tests is challenging, and evidence on discordance between tests in risk stratification presents further dilemmas. We present an approach, modelled in breast cancer, which can provide health care providers and researchers with the potential to perform robust and meaningful comparisons between multigene tests in a cost-effective manner. We demonstrate that whilst viable estimates of gene signatures can be derived from modelling approaches, in our study using a training approach allowed a close approximation to true signature results.

Analytical validation of a standardised scoring protocol for Ki67 immunohistochemistry on breast cancer excision whole sections: an international multicentre collaboration.

AIMS: The nuclear proliferation marker Ki67 assayed by immunohistochemistry has multiple potential uses in breast cancer, but an unacceptable level of interlaboratory variability has hampered its clinical utility. The International Ki67 in Breast Cancer Working Group has undertaken a systematic programme to determine whether Ki67 measurement can be analytically validated and standardised among laboratories. This study addresses whether acceptable scoring reproducibility can be achieved on excision whole sections. METHODS AND RESULTS: Adjacent sections from 30 primary ER+ breast cancers were centrally stained for Ki67 and sections were circulated among 23 pathologists in 12 countries. All pathologists scored Ki67 by two methods: (i) global: four fields of 100 tumour cells each were selected to reflect observed heterogeneity in nuclear staining; (ii) hot-spot: the field with highest apparent Ki67 index was selected and up to 500 cells scored. The intraclass correlation coefficient (ICC) for the global method [confidence interval (CI) = 0.87; 95% CI = 0.799-0.93] marginally met the prespecified success criterion (lower 95% CI ≥ 0.8), while the ICC for the hot-spot method (0.83; 95% CI = 0.74-0.90) did not. Visually, interobserver concordance in location of selected hot-spots varies between cases. The median times for scoring were 9 and 6 min for global and hot-spot methods, respectively. CONCLUSIONS: The global scoring method demonstrates adequate reproducibility to warrant next steps towards evaluation for technical and clinical validity in appropriate cohorts of cases. The time taken for scoring by either method is practical using counting software we are making publicly available. Establishment of external quality assessment schemes is likely to improve the reproducibility between laboratories further.

An international multicenter study to evaluate reproducibility of automated scoring for assessment of Ki67 in breast cancer.

The nuclear proliferation biomarker Ki67 has potential prognostic, predictive, and monitoring roles in breast cancer. Unacceptable between-laboratory variability has limited its clinical value. The International Ki67 in Breast Cancer Working Group investigated whether Ki67 immunohistochemistry can be analytically validated and standardized across laboratories using automated machine-based scoring. Sets of pre-stained core-cut biopsy sections of 30 breast tumors were circulated to 14 laboratories for scanning and automated assessment of the average and maximum percentage of tumor cells positive for Ki67. Seven unique scanners and 10 software platforms were involved in this study. Pre-specified analyses included evaluation of reproducibility between all laboratories (primary) as well as among those using scanners from a single vendor (secondary). The primary reproducibility metric was intraclass correlation coefficient between laboratories, with success considered to be intraclass correlation coefficient >0.80. Intraclass correlation coefficient for automated average scores across 16 operators was 0.83 (95% credible interval: 0.73-0.91) and intraclass correlation coefficient for maximum scores across 10 operators was 0.63 (95% credible interval: 0.44-0.80). For the laboratories using scanners from a single vendor (8 score sets), intraclass correlation coefficient for average automated scores was 0.89 (95% credible interval: 0.81-0.96), which was similar to the intraclass correlation coefficient of 0.87 (95% credible interval: 0.81-0.93) achieved using these same slides in a prior visual-reading reproducibility study. Automated machine assessment of average Ki67 has the potential to achieve between-laboratory reproducibility similar to that for a rigorously standardized pathologist-based visual assessment of Ki67. The observed intraclass correlation coefficient was worse for maximum compared to average scoring methods, suggesting that maximum score methods may be suboptimal for consistent measurement of proliferation. Automated average scoring methods show promise for assessment of Ki67 scoring, but requires further standardization and subsequent clinical validation.

Nottingham Prognostic Index Plus: Validation of a clinical decision making tool in breast cancer in an independent series.

The Nottingham Prognostic Index Plus (NPI+) is a clinical decision making tool in breast cancer (BC) that aims to provide improved patient outcome stratification superior to the traditional NPI. This study aimed to validate the NPI+ in an independent series of BC. Eight hundred and eighty five primary early stage BC cases from Edinburgh were semi-quantitatively assessed for 10 biomarkers [Estrogen Receptor (ER), Progesterone Receptor (PgR), cytokeratin (CK) 5/6, CK7/8, epidermal growth factor receptor (EGFR), HER2, HER3, HER4, p53, and Mucin 1] using immunohistochemistry and classified into biological classes by fuzzy logic-derived algorithms previously developed in the Nottingham series. Subsequently, NPI+ Prognostic Groups (PGs) were assigned for each class using bespoke NPI-like formulae, previously developed in each NPI+ biological class of the Nottingham series, utilising clinicopathological parameters: number of positive nodes, pathological tumour size, stage, tubule formation, nuclear pleomorphism and mitotic counts. Biological classes and PGs were compared between the Edinburgh and Nottingham series using Cramer's V and their role in patient outcome prediction using Kaplan-Meier curves and tested using Log Rank. The NPI+ biomarker panel classified the Edinburgh series into seven biological classes similar to the Nottingham series (p > 0.01). The biological classes were significantly associated with patient outcome (p < 0.001). PGs were comparable in predicting patient outcome between series in Luminal A, Basal p53 altered, HER2+/ER+ tumours (p > 0.01). The good PGs were similarly validated in Luminal B, Basal p53 normal, HER2+/ER- tumours and the poor PG in the Luminal N class (p > 0.01). Due to small patient numbers assigned to the remaining PGs, Luminal N, Luminal B, Basal p53 normal and HER2+/ER- classes could not be validated. This study demonstrates the reproducibility of NPI+ and confirmed its prognostic value in an independent cohort of primary BC. Further validation in large randomised controlled trial material is warranted.

Validation of the IHC4 Breast Cancer Prognostic Algorithm Using Multiple Approaches on the Multinational TEAM Clinical Trial.

CONTEXT: Hormone receptors HER2/neu and Ki-67 are markers of residual risk in early breast cancer. An algorithm (IHC4) combining these markers may provide additional information on residual risk of recurrence in patients treated with hormone therapy. OBJECTIVE: To independently validate the IHC4 algorithm in the multinational Tamoxifen Versus Exemestane Adjuvant Multicenter Trial (TEAM) cohort, originally developed on the trans-ATAC (Arimidex, Tamoxifen, Alone or in Combination Trial) cohort, by comparing 2 methodologies. DESIGN: The IHC4 biomarker expression was quantified on TEAM cohort samples (n = 2919) by using 2 independent methodologies (conventional 3,3'-diaminobezidine [DAB] immunohistochemistry with image analysis and standardized quantitative immunofluorescence [QIF] by AQUA technology). The IHC4 scores were calculated by using the same previously established coefficients and then compared with recurrence-free and distant recurrence-free survival, using multivariate Cox proportional hazards modeling. RESULTS: The QIF model was highly significant for prediction of residual risk (P < .001), with continuous model scores showing a hazard ratio (HR) of 1.012 (95% confidence interval [95% CI]: 1.010-1.014), which was significantly higher than that for the DAB model (HR: 1.008, 95% CI: 1.006-1.009); P < .001). Each model added significant prognostic value in addition to recognized clinical prognostic factors, including nodal status, in multivariate analyses. Quantitative immunofluorescence, however, showed more accuracy with respect to overall residual risk assessment than the DAB model. CONCLUSIONS: The use of the IHC4 algorithm was validated on the TEAM trial for predicting residual risk in patients with breast cancer. These data support the use of the IHC4 algorithm clinically, but quantitative and standardized approaches need to be used.

Analytical validation of a standardized scoring protocol for Ki67: phase 3 of an international multicenter collaboration.

Pathological analysis of the nuclear proliferation biomarker Ki67 has multiple potential roles in breast and other cancers. However, clinical utility of the immunohistochemical (IHC) assay for Ki67 immunohistochemistry has been hampered by unacceptable between-laboratory analytical variability. The International Ki67 Working Group has conducted a series of studies aiming to decrease this variability and improve the evaluation of Ki67. This study tries to assess whether acceptable performance can be achieved on prestained core-cut biopsies using a standardized scoring method. Sections from 30 primary ER+ breast cancer core biopsies were centrally stained for Ki67 and circulated among 22 laboratories in 11 countries. Each laboratory scored Ki67 using three methods: (1) global (4 fields of 100 cells each); (2) weighted global (same as global but weighted by estimated percentages of total area); and (3) hot-spot (single field of 500 cells). The intraclass correlation coefficient (ICC), a measure of interlaboratory agreement, for the unweighted global method (0.87; 95% credible interval (CI): 0.81-0.93) met the prespecified success criterion for scoring reproducibility, whereas that for the weighted global (0.87; 95% CI: 0.7999-0.93) and hot-spot methods (0.84; 95% CI: 0.77-0.92) marginally failed to do so. The unweighted global assessment of Ki67 IHC analysis on core biopsies met the prespecified criterion of success for scoring reproducibility. A few cases still showed large scoring discrepancies. Establishment of external quality assessment schemes is likely to improve the agreement between laboratories further. Additional evaluations are needed to assess staining variability and clinical validity in appropriate cohorts of samples.

An international study to increase concordance in Ki67 scoring.

Although an important biomarker in breast cancer, Ki67 lacks scoring standardization, which has limited its clinical use. Our previous study found variability when laboratories used their own scoring methods on centrally stained tissue microarray slides. In this current study, 16 laboratories from eight countries calibrated to a specific Ki67 scoring method and then scored 50 centrally MIB-1 stained tissue microarray cases. Simple instructions prescribed scoring pattern and staining thresholds for determination of the percentage of stained tumor cells. To calibrate, laboratories scored 18 'training' and 'test' web-based images. Software tracked object selection and scoring. Success for the calibration was prespecified as Root Mean Square Error of scores compared with reference <0.6 and Maximum Absolute Deviation from reference <1.0 (log2-transformed data). Prespecified success criteria for tissue microarray scoring required intraclass correlation significantly >0.70 but aiming for observed intraclass correlation ≥0.90. Laboratory performance showed non-significant but promising trends of improvement through the calibration exercise (mean Root Mean Square Error decreased from 0.6 to 0.4, Maximum Absolute Deviation from 1.6 to 0.9; paired t-test: P=0.07 for Root Mean Square Error, 0.06 for Maximum Absolute Deviation). For tissue microarray scoring, the intraclass correlation estimate was 0.94 (95% credible interval: 0.90-0.97), markedly and significantly >0.70, the prespecified minimum target for success. Some discrepancies persisted, including around clinically relevant cutoffs. After calibrating to a common scoring method via a web-based tool, laboratories can achieve high inter-laboratory reproducibility in Ki67 scoring on centrally stained tissue microarray slides. Although these data are potentially encouraging, suggesting that it may be possible to standardize scoring of Ki67 among pathology laboratories, clinically important discrepancies persist. Before this biomarker could be recommended for clinical use, future research will need to extend this approach to biopsies and whole sections, account for staining variability, and link to outcomes.

Mutational analysis of PI3K/AKT signaling pathway in tamoxifen exemestane adjuvant multinational pathology study.

PURPOSE: Deregulation of key PI3K/AKT pathway genes may contribute to endocrine resistance in breast cancer (BC). PIK3CA is the most frequently mutated gene in luminal BC (35%); however, the effect of mutations in helical versus kinase domains remains controversial. We hypothesize that improved outcomes occur in patients with estrogen receptor­positive (ER positive) BC receiving endocrine therapy and possessing PIK3CA mutations. MATERIALS AND METHODS: DNA was extracted from 4,540 formalin-fixed paraffin-embedded BC samples from the Exemestane Versus Tamoxifen-Exemestane pathology study. Mutational analyses were performed for 25 mutations (PIK3CAx10, AKT1x1, KRASx5, HRASx3, NRASx2 and BRAFx4). RESULTS: PIK3CA mutations were frequent (39.8%), whereas RAS/RAF mutations were rare (1%). In univariable analyses PIK3CA mutations were associated with significantly improved 5-year distant relapse-free survival (DRFS; HR, 0.76; 95% CI, 0.63 to 0.91; P = .003). However, a multivariable analysis correcting for known clinical and biologic prognostic factors failed to demonstrate that PIK3CA mutation status is an independent prognostic marker for DRFS (HR, 0.92; 95% CI, 0.75 to 1.12; P = .4012). PIK3CA mutations were more frequent in low-risk luminal BCs (e.g., grade 1 nodev 3, node-negative v -positive), confounding the relationship between mutations and outcome. CONCLUSION: PIK3CA mutations are present in approximately 40% of luminal BCs but are not an independent predictor of outcome in the context of endocrine therapy, whereas RAS/RAF mutations are rare inluminal BC. A complex relationship between low-risk cancers and PIK3CA mutations was identified. Although the PI3K/AKT pathway remains a viable therapeutic target as the result of ahigh mutation frequency, PIK3CA mutations do not seem to affect residual risk following treatment with endocrine therapy.

An international Ki67 reproducibility study.

BACKGROUND: In breast cancer, immunohistochemical assessment of proliferation using the marker Ki67 has potential use in both research and clinical management. However, lack of consistency across laboratories has limited Ki67's value. A working group was assembled to devise a strategy to harmonize Ki67 analysis and increase scoring concordance. Toward that goal, we conducted a Ki67 reproducibility study. METHODS: Eight laboratories received 100 breast cancer cases arranged into 1-mm core tissue microarrays-one set stained by the participating laboratory and one set stained by the central laboratory, both using antibody MIB-1. Each laboratory scored Ki67 as percentage of positively stained invasive tumor cells using its own method. Six laboratories repeated scoring of 50 locally stained cases on 3 different days. Sources of variation were analyzed using random effects models with log2-transformed measurements. Reproducibility was quantified by intraclass correlation coefficient (ICC), and the approximate two-sided 95% confidence intervals (CIs) for the true intraclass correlation coefficients in these experiments were provided. RESULTS: Intralaboratory reproducibility was high (ICC = 0.94; 95% CI = 0.93 to 0.97). Interlaboratory reproducibility was only moderate (central staining: ICC = 0.71, 95% CI = 0.47 to 0.78; local staining: ICC = 0.59, 95% CI = 0.37 to 0.68). Geometric mean of Ki67 values for each laboratory across the 100 cases ranged 7.1% to 23.9% with central staining and 6.1% to 30.1% with local staining. Factors contributing to interlaboratory discordance included tumor region selection, counting method, and subjective assessment of staining positivity. Formal counting methods gave more consistent results than visual estimation. CONCLUSIONS: Substantial variability in Ki67 scoring was observed among some of the world's most experienced laboratories. Ki67 values and cutoffs for clinical decision-making cannot be transferred between laboratories without standardizing scoring methodology because analytical validity is limited.

Phosphorylation of AKT pathway proteins is not predictive of benefit of taxane therapy in early breast cancer.

Results from the NSABP B-28 trial suggest AKT activation may predict reduced benefit from taxanes following standard anthracycline therapy. Pre-clinical data support a link between PI3 K/AKT signalling and taxane resistance. Using the UK taxotere as adjuvant chemotherapy trial (TACT), we tested the hypothesis that activation of AKT or downstream markers, p70S6K or p90RSK, identifies patients with reduced benefit from taxane chemotherapy. TACT is a multi-centre open-label phase III trial comparing four cycles of standard FEC (fluorouracil, epirubicin, cyclophosphamide) followed by four cycles of docetaxel versus eight cycles of anthracycline-based chemotherapy. Samples from 3,596 patients were available for the current study. We performed immunohistochemical analysis of activation of AKT, p70S6 K and p90RSK. Using a training set with multiple cut-offs for predictive values (10 % increments in expression), we found no evidence for a treatment by marker interaction for pAKT473, pS6 or p90RSK. pAKT473, pS6 and p90RSK expression levels were weakly correlated. A robust, preplanned statistical analysis in the TACT trial found no evidence that pAKT473, pS6 or p90RSK identifies patients deriving reduced benefit from adjuvant docetaxel. This result is consistent with the recent NASBP B28 study where the pAKT473 effect is not statistically significant for the treatment interaction test. Therefore, neither TACT nor NASBP-B28 provides statistically robust evidence of a treatment by marker interaction between pAKT473 and taxane treatment. Alternative methods for selecting patients benefitting from taxanes should be explored.

Mammostrat as an immunohistochemical multigene assay for prediction of early relapse risk in the tamoxifen versus exemestane adjuvant multicenter trial pathology study.

PURPOSE: Some postmenopausal patients with hormone-sensitive early breast cancer remain at high risk of relapse despite endocrine therapy and, in addition, might benefit from adjuvant chemotherapy. The challenge is to prospectively identify such patients. The Mammostrat test uses five immunohistochemical markers to stratify patients regarding recurrence risk and may inform treatment decisions. We tested the efficacy of this panel in the Tamoxifen versus Exemestane Adjuvant Multicenter (TEAM) trial. PATIENTS AND METHODS: Pathology blocks from 4,598 TEAM patients were collected, and tissue microarrays (TMAs) were constructed. The cohort was 47% node-positive, and 36% of patients in the cohort were treated with adjuvant chemotherapy. Triplicate 0.6-mm(2) TMA cores were stained, and positivity for p53, HTF9C, CEACAM5, NDRG1, and SLC7A5 was assessed. Cases were assigned a Mammostrat risk score, and distant relapse-free survival (DRFS) and disease-free survival (DFS) were analyzed. RESULTS: In multivariate regression analyses, which were corrected for conventional clinicopathologic markers, Mammostrat provided significant additional information on DRFS after endocrine therapy in estrogen receptor (ER) -positive node-negative patients (n = 1,226) who did not receive chemotherapy (P = .004). Additional analyses in all patients not exposed to chemotherapy, irrespective of nodal status (n = 2,559) and in the entire cohort (n = 3,837) showed Mammostrat scores provided additional information on DRFS in these groups (P = .001 and P < .001, respectively; multivariate analyses). No differences were seen between the two endocrine treatment regimens. CONCLUSION: The Mammostrat score predicts DRFS for patients treated with exemestane and patients treated with tamoxifen followed by exemestane irrespective of nodal status and chemotherapy. The ability of this test to provide additional outcome data after treatment provides additional evidence of its use in risk stratification of ER-positive postmenopausal patients with breast cancer.