Non-linear transformations of age at diagnosis, tumor size, and number of positive lymph nodes in prediction of clinical outcome in breast cancer.

BACKGROUND: Prognostic factors in breast cancer are often measured on a continuous scale, but categorized for clinical decision-making. The primary aim of this study was to evaluate if accounting for continuous non-linear effects of the three factors age at diagnosis, tumor size, and number of positive lymph nodes improves prognostication. These factors will most likely be included in the management of breast cancer patients also in the future, after an expected implementation of gene expression profiling for adjuvant treatment decision-making. METHODS: Four thousand four hundred forty seven and 1132 women with primary breast cancer constituted the derivation and validation set, respectively. Potential non-linear effects on the log hazard of distant recurrences of the three factors were evaluated during 10 years of follow-up. Cox-models of successively increasing complexity: dichotomized predictors, predictors categorized into three or four groups, and predictors transformed using fractional polynomials (FPs) or restricted cubic splines (RCS), were used. Predictive performance was evaluated by Harrell's C-index. RESULTS: Using FP-transformations, non-linear effects were detected for tumor size and number of positive lymph nodes in univariable analyses. For age, non-linear transformations did, however, not improve the model fit significantly compared to the linear identity transformation. As expected, the C-index increased with increasing model complexity for multivariable models including the three factors. By allowing more than one cut-point per factor, the C-index increased from 0.628 to 0.674. The additional gain, as measured by the C-index, when using FP- or RCS-transformations was modest (0.695 and 0.696, respectively). The corresponding C-indices for these four models in the validation set, based on the same transformations and parameter estimates from the derivation set, were 0.675, 0.700, 0.706, and 0.701. CONCLUSIONS: Categorization of each factor into three to four groups was found to improve prognostication compared to dichotomization. The additional gain by allowing continuous non-linear effects modeled by FPs or RCS was modest. However, the continuous nature of these transformations has the advantage of making it possible to form risk groups of any size.

Clinical Value of RNA Sequencing-Based Classifiers for Prediction of the Five Conventional Breast Cancer Biomarkers: A Report From the Population-Based Multicenter Sweden Cancerome Analysis Network-Breast Initiative.

PURPOSE: In early breast cancer (BC), five conventional biomarkers-estrogen receptor (ER), progesterone receptor (PgR), human epidermal growth factor receptor 2 (HER2), Ki67, and Nottingham histologic grade (NHG)-are used to determine prognosis and treatment. We aimed to develop classifiers for these biomarkers that were based on tumor mRNA sequencing (RNA-seq), compare classification performance, and test whether such predictors could add value for risk stratification. METHODS: In total, 3,678 patients with BC were studied. For 405 tumors, a comprehensive multi-rater histopathologic evaluation was performed. Using RNA-seq data, single-gene classifiers and multigene classifiers (MGCs) were trained on consensus histopathology labels. Trained classifiers were tested on a prospective population-based series of 3,273 BCs that included a median follow-up of 52 months (Sweden Cancerome Analysis Network-Breast [SCAN-B], ClinicalTrials.gov identifier: NCT02306096), and results were evaluated by agreement statistics and Kaplan-Meier and Cox survival analyses. RESULTS: Pathologist concordance was high for ER, PgR, and HER2 (average κ, 0.920, 0.891, and 0.899, respectively) but moderate for Ki67 and NHG (average κ, 0.734 and 0.581). Concordance between RNA-seq classifiers and histopathology for the independent cohort of 3,273 was similar to interpathologist concordance. Patients with discordant classifications, predicted as hormone responsive by histopathology but non-hormone responsive by MGC, had significantly inferior overall survival compared with patients who had concordant results. This extended to patients who received no adjuvant therapy (hazard ratio [HR], 3.19; 95% CI, 1.19 to 8.57), or endocrine therapy alone (HR, 2.64; 95% CI, 1.55 to 4.51). For cases identified as hormone responsive by histopathology and who received endocrine therapy alone, the MGC hormone-responsive classifier remained significant after multivariable adjustment (HR, 2.45; 95% CI, 1.39 to 4.34). CONCLUSION: Classification error rates for RNA-seq-based classifiers for the five key BC biomarkers generally were equivalent to conventional histopathology. However, RNA-seq classifiers provided added clinical value in particular for tumors determined by histopathology to be hormone responsive but by RNA-seq to be hormone insensitive.

An inter-observer Ki67 reproducibility study applying two different assessment methods: on behalf of the Danish Scientific Committee of Pathology, Danish breast cancer cooperative group (DBCG).

INTRODUCTION: In 2011, the St. Gallen Consensus Conference introduced the use of pathology to define the intrinsic breast cancer subtypes by application of immunohistochemical (IHC) surrogate markers ER, PR, HER2 and Ki67 with a specified Ki67 cutoff (>14%) for luminal B-like definition. Reports concerning impaired reproducibility of Ki67 estimation and threshold inconsistency led to the initiation of this quality assurance study (2013-2015). The aim of the study was to investigate inter-observer variation for Ki67 estimation in malignant breast tumors by two different quantification methods (assessment method and count method) including measure of agreement between methods. MATERIAL AND METHODS: Fourteen experienced breast pathologists from 12 pathology departments evaluated 118 slides from a consecutive series of malignant breast tumors. The staining interpretation was performed according to both the Danish and Swedish guidelines. Reproducibility was quantified by intra-class correlation coefficient (ICC) and Lights Kappa with dichotomization of observations at the larger than (>) 20% threshold. The agreement between observations by the two quantification methods was evaluated by Bland-Altman plot. RESULTS: For the fourteen raters the median ranged from 20% to 40% by the assessment method and from 22.5% to 36.5% by the count method. Light's Kappa was 0.664 for observation by the assessment method and 0.649 by the count method. The ICC was 0.82 (95% CI: 0.77-0.86) by the assessment method vs. 0.84 (95% CI: 0.80-0.87) by the count method. CONCLUSION: Although the study in general showed a moderate to good inter-observer agreement according to both ICC and Lights Kappa, still major discrepancies were identified in especially the mid-range of observations. Consequently, for now Ki67 estimation is not implemented in the DBCG treatment algorithm.

Histological grade provides significant prognostic information in addition to breast cancer subtypes defined according to St Gallen 2013.

BACKGROUND: The St Gallen surrogate definition of the intrinsic subtypes of breast cancer consist of five subgroups based on estrogen receptor (ER), progesterone receptor (PgR), human epidermal growth factor receptor type 2 (HER2), and Ki-67. PgR and Ki-67 are used for discriminating between the 'Luminal A-like' and 'Luminal B-like (HER2-negative)' subtypes. Histological grade (G) has prognostic value in breast cancer; however, its relationship to the St Gallen subtypes is not clear. Based on a previous pilot study, we hypothesized that G could be a primary discriminator for ER-positive/HER2-negative breast cancers that were G1 or G3, whereas Ki-67 and PgR could provide additional prognostic information specifically for patients with G2 tumors. To test this hypothesis, a larger patient cohort was examined. PATIENTS AND METHODS: Six hundred seventy-one patients (≥35 years of age, pT1-2, pN0-1) with ER-positive/HER2-negative breast cancer and complete data for PgR, Ki-67, G, lymph node status, tumor size, age, and distant disease-free survival (DDFS; median follow-up 9.2 years) were included. RESULTS: 'Luminal A-like' tumors were mostly G1 or G2 (90%) whereas 'Luminal B-like' tumors were mostly G2 or G3 (87%) and corresponded with good and poor DDFS, respectively. In 'Luminal B-like' tumors that were G1 (n = 23), no metastasis occurred, whereas 14 of 40 'Luminal A-like' tumors that were G3 metastasized. In the G2 subgroup, low PgR and high Ki-67 were associated with an increased risk of distant metastases, hazard ratio (HR) and 95% confidence interval (CI) 1.8 (0.95-3.4) and 1.5 (0.80-2.8), respectively. CONCLUSIONS: Patients with ER-positive/HER2-negative/G1 breast cancer have a good prognosis, similar to that of 'Luminal A-like', while those with ER-positive/HER2-negative/G3 breast cancer have a worse prognosis, similar to that of 'Luminal B-like', when assessed independently of PgR and Ki-67. Therapy decisions based on Ki-67 and PgR might thus be restricted to the subgroup G2.

The accuracy of preoperative axillary nodal staging in primary breast cancer by ultrasound is modified by nodal metastatic load and tumor biology.

Background The outcome of axillary ultrasound (AUS) with fine-needle aspiration biopsy (FNAB) in the diagnostic work-up of primary breast cancer has an impact on therapy decisions. We hypothesize that the accuracy of AUS is modified by nodal metastatic burden and clinico-pathological characteristics. Material and methods The performance of AUS and AUS-guided FNAB for predicting nodal metastases was assessed in a prospective breast cancer cohort subjected for surgery during 2009-2012. Predictors of accuracy were included in multivariate analysis. Results AUS had a sensitivity of 23% and a specificity of 95%, while AUS-guided FNAB obtained 73% and 100%, respectively. AUS-FNAB exclusively detected macro-metastases (median four metastases) and identified patients with more extensive nodal metastatic burden in comparison with sentinel node biopsy. The accuracy of AUS was affected by metastatic size (OR 1.11), obesity (OR 2.46), histological grade (OR 4.43), and HER2-status (OR 3.66); metastatic size and histological grade were significant in the multivariate analysis. Conclusions The clinical utility of AUS in low-risk breast cancer deserves further evaluation as the accuracy decreased with a low nodal metastatic burden. The diagnostic performance is modified by tumor and clinical characteristics. Patients with nodal disease detected by AUS-FNAB represent a group for whom neoadjuvant therapy should be considered.

Localization of tamoxifen in human breast cancer tumors by MALDI mass spectrometry imaging.

BACKGROUND: Tamoxifen is used in endocrine treatment of breast cancer to inhibit estrogen signaling. A set of stratified ER-positive and ER-negative tumor sections was subjected to manual deposition of tamoxifen solution in order to investigate its spatial distribution upon exposure to interaction within thin tissue sections. METHODS: The localization of tamoxifen in tumor sections was assessed by matrix assisted laser deposition/ionization mass spectrometry imaging. The images of extracted ion maps were analyzed for comparison of signal intensity distributions. RESULTS: The precursor ion of tamoxifen (m/z 372.233) displayed heterogeneous signal intensity distributions in histological compartments of tumor tissue sections. The levels of tamoxifen in tumor cells compared with stroma were higher in ER-positive tissues, whereas ER-negative tissue sections showed lower signal intensities in tumor cells. CONCLUSIONS: The experimental model was successfully applied on frozen tumor samples allowing for differentiation between ER groups based on distribution of tamoxifen.

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.

Remarkable similarities of chromosomal rearrangements between primary human breast cancers and matched distant metastases as revealed by whole-genome sequencing.

To better understand and characterize chromosomal structural variation during breast cancer progression, we enumerated chromosomal rearrangements for 11 patients by performing low-coverage whole-genome sequencing of 11 primary breast tumors and their 13 matched distant metastases. The tumor genomes harbored a median of 85 (range 18-404) rearrangements per tumor, with a median of 82 (26-310) in primaries compared to 87 (18-404) in distant metastases. Concordance between paired tumors from the same patient was high with a median of 89% of rearrangements shared (range 61-100%), whereas little overlap was found when comparing all possible pairings of tumors from different patients (median 3%). The tumors exhibited diverse genomic patterns of rearrangements: some carried events distributed throughout the genome while others had events mostly within densely clustered chromothripsis-like foci at a few chromosomal locations. Irrespectively, the patterns were highly conserved between the primary tumor and metastases from the same patient. Rearrangements occurred more frequently in genic areas than expected by chance and among the genes affected there was significant enrichment for cancer-associated genes including disruption of TP53, RB1, PTEN, and ESR1, likely contributing to tumor development. Our findings are most consistent with chromosomal rearrangements being early events in breast cancer progression that remain stable during the development from primary tumor to distant metastasis.

Stem cell biomarker ALDH1A1 in breast cancer shows an association with prognosis and clinicopathological variables that is highly cut-off dependent.

AIMS: Aldehyde dehydrogenase family 1 member A1 (ALDH1A1) is a putative marker of breast cancer stem cells (CSCs) with prognostic implications when expressed in cancer or stroma. However, previous results are contradictory and we therefore aimed to further evaluate the impact of ALDH1A1 on distant disease-free survival (DDFS) and correlation with clinicopathological variables in breast cancer, specifically by evaluating different cut-offs. METHODS: Two breast cancer cohorts (N=216 and N=210) were evaluated with immunohistochemistry for ALDH1A1 on tissue microarrays with three different cut-offs in cancer cells and in stromal cells. The association of ALDH1A1 with DDFS and other clinicopathological variables was assessed. As further validation, gene expression levels of ALDH1A1 and association with survival were analysed in one of the cohorts and a separate cohort. RESULTS: ALDH1A1 expression in cancer cells was associated with either a better or a worse prognosis, depending on cut-off. Considering weakly stained cancer cells as positive, ALDH1A1+ was associated with a better prognosis in both cohorts. Considering only strongly stained cells as positive, ALDH1A1+ was associated with oestrogen receptor and progesterone receptor negativity in both cohorts and worse prognosis in one of the cohorts. Stromal ALDH1A1 staining was associated with improved DDFS in one cohort. Gene expression analysis showed that a high ALDH1A1 expression was associated with a better prognosis. CONCLUSIONS: ALDH1A1 is associated with DDFS and clinicopathological variables, both in cancer cells and stroma, but is highly cut-off dependent. Only the strongly ALDH1A1-stained cells show a more aggressive phenotype typical for CSCs.

Highly reproducible results of breast cancer biomarkers when analysed in accordance with national guidelines - a Swedish survey with central re-assessment.

BACKGROUND: Biomarkers are crucial for decisions regarding adjuvant therapy in primary breast cancer, and their correct assessment is therefore of the utmost importance. AIMS: To investigate the concordance between Swedish pathology departments and a reference laboratory, for routine analysis of oestrogen receptor (ER), progesterone receptor (PR), Ki67, and human epidermal growth factor receptor 2 (HER2), alone, and in combination (St Gallen subtypes). METHODS: This survey included 27 of the 28 pathology laboratories in Sweden, covering 98% of cases of primary breast cancer surgery in Sweden. Paraffin-embedded tumour blocks (n = 270) were collected and sent to the central reference laboratory, together with the originally stained slides, for re-analysis. The primary evaluations were previously performed according to national Swedish guidelines, without any knowledge of the subsequent central assessment. RESULTS: The agreement for ER, PR, and Ki67 was 99% [kappa value (κ) = 0.95], 95% (κ = 0.85), and 85% (κ = 0.70), respectively. The agreement for HER2 (0/1 + vs. 2+/3+) was 85% (κ = 0.64), but when equivocal tumours were further analysed with in situ hybridisation, only one discrepancy was observed. Discrepancies between results for ER and PR seem to be explained by analytical differences, whereas the interpretation of staining seems to be more critical for Ki67 and HER2 immunohistochemistry. The agreement between the results from the Swedish laboratories and the reference laboratory, based on the St Gallen subtypes, was 88% (κ = 0.81). CONCLUSIONS: When applying national guidelines, highly reproducible results were obtained in routine assessment of breast cancer biomarkers, and the results of this study confirm the clinical utility of these markers for decisions regarding the treatment of primary breast cancer.

Changes in glycoprotein expression between primary breast tumour and synchronous lymph node metastases or asynchronous distant metastases.

BACKGROUND: Breast cancer is a very heterogeneous disease and some patients are cured by the surgical removal of the primary tumour whilst other patients suffer from metastasis and spreading of the disease, despite adjuvant therapy. A number of prognostic and treatment predictive factors have been identified such as tumour size, oestrogen (ER) and progesterone (PgR) receptor status, human epidermal growth factor receptor type 2 (HER2) status, histological grade, Ki67 and age. Lymph node involvement is also assessed during surgery to determine if the tumour has spread which requires dissection of the axilla and adjuvant treatment. The prognostic and treatment predictive factors assessing the nature of the tumour are all routinely based on the status of the primary tumour. RESULTS: We have analysed a unique tumour set of fourteen primary breast cancer tumours with matched synchronous axillary lymph node metastases and a set of nine primary tumours with, later developed, matched distant metastases from different sites in the body. We used a pairwise tumour analysis (from the same individual) since the difference between the same tumour-type in different patients was greater. Glycopeptide capture was used in this study to selectively isolate and quantify N-linked glycopeptides from tumours mixtures and the captured glycopeptides were subjected to label-free quantitative tandem mass spectrometry analysis. Differentially expressed proteins between primary tumours and matched lymph node metastasis and distant metastasis were identified. Two of the top hits, ATPIF1 and tubulin ß-chain were validated by immunohistochemistry to be differentially regulated. CONCLUSIONS: We show that the expression of a large number of glycosylated proteins change between primary tumours and matched lymph node metastases and distant metastases, confirming that cancer cells undergo a molecular transformation during the spread to a secondary site. The proteins are part of important pathways such as cell adhesion, migration pathways and immune response giving insight into molecular changes needed for the tumour to spread. The large difference between primary tumours and lymph node and distant metastases also suggest that treatment should be based on the phenotype of the lymph node and distant metastases.

Serial monitoring of circulating tumor DNA in patients with primary breast cancer for detection of occult metastatic disease.

Metastatic breast cancer is usually diagnosed after becoming symptomatic, at which point it is rarely curable. Cell-free circulating tumor DNA (ctDNA) contains tumor-specific chromosomal rearrangements that may be interrogated in blood plasma. We evaluated serial monitoring of ctDNA for earlier detection of metastasis in a retrospective study of 20 patients diagnosed with primary breast cancer and long follow-up. Using an approach combining low-coverage whole-genome sequencing of primary tumors and quantification of tumor-specific rearrangements in plasma by droplet digital PCR, we identify for the first time that ctDNA monitoring is highly accurate for postsurgical discrimination between patients with (93%) and without (100%) eventual clinically detected recurrence. ctDNA-based detection preceded clinical detection of metastasis in 86% of patients with an average lead time of 11 months (range 0-37 months), whereas patients with long-term disease-free survival had undetectable ctDNA postoperatively. ctDNA quantity was predictive of poor survival. These findings establish the rationale for larger validation studies in early breast cancer to evaluate ctDNA as a monitoring tool for early metastasis detection, therapy modification, and to aid in avoidance of overtreatment.

Statin-induced anti-proliferative effects via cyclin D1 and p27 in a window-of-opportunity breast cancer trial.

PURPOSE: Cholesterol lowering statins have been demonstrated to exert anti-tumoral effects on breast cancer by decreasing proliferation as measured by Ki67. The biological mechanisms behind the anti-proliferative effects remain elusive. The aim of this study was to investigate potential statin-induced effects on the central cell cycle regulators cyclin D1 and p27. EXPERIMENTAL DESIGN: This phase II window-of-opportunity trial (Trial registration: ClinicalTrials.gov NCT00816244 , NIH) included 50 patients with primary invasive breast cancer. High-dose atorvastatin (80 mg/day) was prescribed to patients for two weeks prior to surgery. Paired paraffin embedded pre- and post-statin treatment tumor samples were analyzed using immunohistochemistry for the expression of estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2), and the cell cycle regulators cyclin D1 and p27. Corresponding frozen tumor sample pairs were analyzed for expression of the genes coding for cyclin D1 and p27, CCND1 and CDKN1B, respectively. RESULTS: Forty-two patients completed all study parts, and immunohistochemical evaluation of ER and PR was achievable in 30 tumor pairs, HER2 in 29 tumor pairs, cyclin D1 in 30 tumor pairs and p27 in 33 tumor pairs. The expression of ER, PR and HER2 did not change significantly following atorvastatin treatment. Cyclin D1 expression in terms of nuclear intensity was significantly decreased (P = 0.008) after statin treatment in paired tumor samples. The protein expression of the tumor suppressor p27, evaluated either as the fraction of stained tumor cells or as cytoplasmic intensity, increased significantly (P = 0.03 and P = 0.02, respectively). At the transcriptional level, no significant differences in mRNA expression were detected for cyclin D1 (CCND1) and p27 (CDKN1B). However, CCND1 expression was lower in tumors responding to atorvastatin treatment with a decrease in proliferation although not significantly (P = 0.08). CONCLUSIONS: We have previously reported statin-induced anti-proliferative effects in breast cancer. This study suggests that cell cycle regulatory effects may contribute to these anti-proliferative effects via cyclin D1 and p27.

Global Transcriptional Changes Following Statin Treatment in Breast Cancer.

BACKGROUND: Statins purportedly exert antitumoral effects, but the underlying mechanisms are currently not fully elucidated. The aim of this study was to explore potential statin-induced effects on global gene expression profiles in primary breast cancer. EXPERIMENTAL DESIGN: This window-of-opportunity phase II trial enrolled 50 newly diagnosed breast cancer patients prescribed atorvastatin (80 mg/day) for 2 weeks presurgically. Pre- and posttreatment tumor samples were analyzed using Significance Analysis of Microarrays (SAM) to identify differentially expressed genes. Similarly, SAM and gene ontology analyses were applied to gene expression data derived from atorvastatin-treated breast cancer cell lines (MCF7, BT474, SKBR3, and MDAMB231) comparing treated and untreated cells. The Systematic Motif Analysis Retrieval Tool (SMART) was used to identify enriched transcription factor-binding sites. Literature Vector Analysis (LitVAn) identified gene module functionality, and pathway analysis was performed using GeneGo Pathways Software (MetaCore; https://portal.genego.com/). RESULTS: Comparative analysis of gene expression profiles in paired clinical samples revealed 407 significantly differentially expressed genes (FDR = 0); 32 upregulated and 375 downregulated genes. Restricted filtration (fold change ≥1.49) resulted in 21 upregulated and 46 downregulated genes. Significantly upregulated genes included DUSP1, RHOB1, GADD45B, and RGS1. Pooled results from gene ontology, LitVAn and SMART analyses identified statin-induced effects on the apoptotic and MAPK pathways among others. Comparative analyses of gene expression profiles in breast cancer cell lines showed significant upregulation of the mevalonate and proapoptotic pathways following atorvastatin treatment. CONCLUSIONS: We report potential statin-induced changes in global tumor gene expression profiles, indicating MAPK pathway inhibition and proapoptotic events.

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.

The Sweden Cancerome Analysis Network - Breast (SCAN-B) Initiative: a large-scale multicenter infrastructure towards implementation of breast cancer genomic analyses in the clinical routine.

BACKGROUND: Breast cancer exhibits significant molecular, pathological, and clinical heterogeneity. Current clinicopathological evaluation is imperfect for predicting outcome, which results in overtreatment for many patients, and for others, leads to death from recurrent disease. Therefore, additional criteria are needed to better personalize care and maximize treatment effectiveness and survival. METHODS: To address these challenges, the Sweden Cancerome Analysis Network - Breast (SCAN-B) consortium was initiated in 2010 as a multicenter prospective study with longsighted aims to analyze breast cancers with next-generation genomic technologies for translational research in a population-based manner and integrated with healthcare; decipher fundamental tumor biology from these analyses; utilize genomic data to develop and validate new clinically-actionable biomarker assays; and establish real-time clinical implementation of molecular diagnostic, prognostic, and predictive tests. In the first phase, we focus on molecular profiling by next-generation RNA-sequencing on the Illumina platform. RESULTS: In the first 3 years from 30 August 2010 through 31 August 2013, we have consented and enrolled 3,979 patients with primary breast cancer at the seven hospital sites in South Sweden, representing approximately 85% of eligible patients in the catchment area. Preoperative blood samples have been collected for 3,942 (99%) patients and primary tumor specimens collected for 2,929 (74%) patients. Herein we describe the study infrastructure and protocols and present initial proof of concept results from prospective RNA sequencing including tumor molecular subtyping and detection of driver gene mutations. Prospective patient enrollment is ongoing. CONCLUSIONS: We demonstrate that large-scale population-based collection and RNA-sequencing analysis of breast cancer is feasible. The SCAN-B Initiative should significantly reduce the time to discovery, validation, and clinical implementation of novel molecular diagnostic and predictive tests. We welcome the participation of additional comprehensive cancer treatment centers. TRIAL REGISTRATION: ClinicalTrials.gov identifier NCT02306096.

The three receptor tyrosine kinases c-KIT, VEGFR2 and PDGFRα, closely spaced at 4q12, show increased protein expression in triple-negative breast cancer.

BACKGROUND: Triple-negative breast cancer (TNBC) is a heterogeneous subgroup of breast cancer with poor prognosis and no targeted therapy available. Receptor tyrosine kinases (RTKs) are emerging targets in anticancer therapy and many RTK-inhibiting drugs are currently being developed. The aim of this study was to elucidate if there is a correlation between the protein expression of three RTKs c-KIT, VEGFR2 and PDGFRα, their gene copy number, and prognosis in TNBC compared to non-TNBC. METHODS: Tumor tissue samples from patients diagnosed with primary breast cancer were stained with immunohistochemistry (IHC) for protein assessment, and with fluorescence in situ hybridization (FISH) for gene copy number determination. Breast cancer mortality (BCM), measured from the date of surgery to death, was used as endpoint. RESULTS: The cohort included 464 patients, out of which 34 (7.3%) had a TNBC. High expression of the three RTKs was more common in TNBC compared to non-TNBC: c-KIT 49% vs. 10% (P<0.001), PDGFRα 32% vs. 19% (P = 0.07) and VEGFR2 32% vs. 6% (P<0.001). The odds ratio (OR) of c-KIT, VEGFR2 and PDGFRα positivity, adjusted for tumor characteristics, was 6.8, 3.6 and 1.3 times higher for TNBC than for non-TNBC. 73.5% of the TNBC had high expression of at least one of the three investigated receptors, compared to 30.0% of the non-TNBC (P<0.001). Survival analysis showed no significant difference in BCM for TNBC patients with high vs. low c-KIT, PDGFRα or VEGFR2 protein expression. 193 (42%) tumors were evaluated with FISH. No correlation was seen between increased gene copy number and TNBC, or between increased gene copy number and high protein expression of the RTK. CONCLUSION: c-KIT, VEGFR2 and PDGFRα show higher protein expression in TNBC compared to non-TNBC. Further investigation clarifying the importance of these RTKs in TNBC is encouraged, as they are possible targets for anticancer therapy.

A novel model for Ki67 assessment in breast cancer.

BACKGROUND: Ki67 is currently the proliferation biomarker of choice, with both prognostic and predictive value in breast cancer. A lack of consensus regarding Ki67 use in pre-analytical, analytical and post-analytical practice may hinder its formal acceptance in the clinical setting. METHODS: One hundred breast cancer samples were stained for Ki67. A standard estimation of Ki67 using fixed denominators of 200, 400 and 1 000 counted tumor cells was performed, and a cut-off at 20% was applied, Ki67static. A novel stepwise counting strategy for Ki67 estimation, Ki67scs, was developed based on rejection regions derived from exact two-sided binomial confidence intervals for proportions. Ki67scs was defined by the following parameters: the cut-off (20%), minimum (50) and maximum (400) number of tumor cells to count, increment (10) and overall significance level of the test procedure (0.05). Results from Ki67scs were compared to results from the Ki67static estimation with fixed denominators. RESULTS: For Ki67scs, the median number of tumor cells needed to determine Ki67 status was 100; the average, 175. Among 38 highly proliferative samples, the average Ki67scs fraction was 45%. For these samples, the fraction decreased from 39% to 37% to 35% with static counting of 200, 400 and 1 000 cells, respectively. The largest absolute difference between the estimation methods was 23% (42% (Ki67scs) vs. 19% (Ki67static)) and resulted in an altered sample classification. Among the 82 unequivocal samples, 74 samples received the same classification using both Ki67scs and Ki67static. Of the eight disparate samples, seven were classified highly proliferative by Ki67static when 200 cells were counted; whereas all eight cases were classified as low proliferative when 1 000 cells were counted. CONCLUSIONS: Ki67 estimation using fixed denominators may be inadequate, particularly for tumors demonstrating extensive heterogeneity. We propose a time saving stepwise counting strategy, which acknowledges small highly proliferative hot spots. VIRTUAL SLIDES: The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/3588156111195336.

The HER2-encoded miR-4728-3p regulates ESR1 through a non-canonical internal seed interaction.

Since the early 1980s remarkable progress has been made in understanding the role of the HER2 locus in carcinogenesis, but many details of its regulatory network are still elusive. We recently reported the finding of 367 new human microRNA (miRNA) genes of which one, mir-4728, is encoded in an intron of the HER2 gene. Here, we confirm that the HER2 oncogene is a bi-functional locus encoding the membrane receptor and a functional miRNA gene. We further show that miR-4728-3p has alternative functionalities depending on the region used for interaction with its target; the canonical seed between nucleotides 2-8 or a novel, more internal seed shifted to nucleotides 6-12. Analysis of public data shows that this internal seed region, although rare compared to the far more abundant canonical 2-8 seed interaction, can also direct targeted down-regulation by other miRNAs. Through the internal seed, miR-4728-3p regulates expression of estrogen receptor alpha, an interaction that would have remained undetected if classic rules for miRNA-target interaction had been applied. In summary, we present here an alternative mode of miRNA regulation and demonstrate this dual function of the HER2 locus, linking the two major biomarkers in breast cancer.

Lack of G protein-coupled estrogen receptor (GPER) in the plasma membrane is associated with excellent long-term prognosis in breast cancer.

G protein-coupled estrogen receptor (GPER), or GPR30, is a membrane receptor reported to mediate non-genomic estrogen responses. Tamoxifen is a partial agonist at GPER in vitro. Here, we investigated if GPER expression is prognostic in primary breast cancer, if the receptor is treatment-predictive for adjuvant tamoxifen, and if receptor subcellular localization has any impact on the prognostic value. Total and plasma membrane (PM) GPER expression was analyzed by immunohistochemistry in breast tumors from 742 postmenopausal lymph node-negative patients subsequently randomized for tamoxifen treatment for 2-5 years versus no systemic treatment, regardless of estrogen receptor (ER) status, and with a median follow-up of 17 years for patients free of event. PM GPER expression was a strong independent prognostic factor for poor prognosis in breast cancer without treatment-predictive information for tamoxifen. In the tamoxifen-treated ER-positive and progesterone receptor (PgR)-positive patient subgroup, the absence of PM GPER (53 % of all ER-positive tumors) predicted 91 % 20-year distant disease-free survival, compared to 73 % in the presence of GPER (p = 0.001). Total GPER expression showed positive correlations with ER and PgR and negative correlation with histological grade, but the correlations were biphasic. On the other hand, PM GPER expression showed strong negative correlations with ER and PgR, and strong positive correlation with HER2 overexpression and high histological grade. GPER overexpression and PM localization are critical events in breast cancer progression, and lack of GPER in the PM is associated with excellent long-term prognosis in ER-positive and PgR-positive tamoxifen-treated primary breast cancer.