The Clinical and Biological Significance of Estrogen Receptor-Low Positive Breast Cancer.

Estrogen receptor (ER) status in breast cancer (BC) is determined using immunohistochemistry (IHC) with nuclear expression in ≥1% of cells defined as ER-positive. BC with 1%-9% expression (ER-low-positive), is a clinically and biologically unique subgroup. In this study, we hypothesized that ER-low-positive BC represents a heterogeneous group with a mixture of ER-positive and ER-negative tumor, which may explain their divergent clinical behavior. A large BC cohort (n = 8171) was investigated and categorized into 3 groups: ER-low-positive (1%-9%), ER-positive (≥10%), and ER-negative (<1%) where clinicopathological and outcome characteristics were compared. A subset of ER-low-positive cases was further evaluated using IHC, RNAscope, and RT-qPCR. PAM50 subtyping and ESR1 mRNA expression levels were assessed in ER-low-positive cases within The Cancer Genome Atlas data set. The reliability of image analysis software in assessment of ER expression in the ER-low-positive category was also assessed. ER-low-positive tumors constituted <2% of BC cases examined and showed significant clinicopathological similarity to ER-negative tumors. Most of these tumors were nonluminal types showing low ESR1 mRNA expression. Further validation of ER status revealed that 45% of these tumors were ER-negative with repeated IHC staining and confirmed by RNAscope and RT-qPCR. ER-low-positive tumors diagnosed on needle core biopsy were enriched with false-positive ER staining. BCs with 10% ER behaved similar to ER-positive, rather than ER-negative or low-positive BCs. Moderate concordance was found in assessment of ER-low-positive tumors, and this was not improved by image analysis. Routinely diagnosed ER-low-positive BC includes a proportion of ER-negative cases. We recommend repeat testing of BC showing 1%-9% ER expression and using a cutoff ≥10% expression to define ER positivity to help better inform treatment decisions.

The prognostic significance of BMI1 expression in invasive breast cancer is dependent on its molecular subtypes.

PURPOSE: BMI1, which is a major component of the polycomb group complex 1, is an essential epigenetic repressor of multiple regulatory genes and has been identified as a cancer stem cell (CSC) marker in several cancers. However, its role in breast cancer (BC) remains to be defined. In this study, we have evaluated the prognostic significance of BMI1 among the different molecular subtypes and assessed its association with other breast CSC markers (BCSC). MATERIAL AND METHOD: BMI1 copy number and mRNA was assessed in large and well-characterised cohorts of early-stage BC patients [METABRIC (n = 1980) and the Bc-GenExMiner (n = 9616) databases]. BMI1 protein expression was assessed using tissue microarray and immunohistochemistry in a cohort of 870 invasive BC patients with long-term outcome data and the expression of a panel of BCSC markers was monitored. RESULT: BMI1 expression, prognostic significance and its association with BCSC markers were differed between molecular classes. In the luminal oestrogen receptor-positive (ER+) BC, BMI1 showed significantly higher expression compared to ER- tumours. BMI1 showed positive correlation with favourable prognostic features and it was negatively associated with the expression of key BCSC markers (ALDH1A1, CD24, CD44, CD133, SOX10 and SOX9). High expression of BMI1 was associated with longer breast cancer-specific survival (BCSS) independent of other prognostic variables. In the basal triple negative BC subtype, BMI1 expression showed positive association with CD133 and SOX10 and it was significantly associated with shorter BCSS. CONCLUSION: High BMI1 expression is associated with clinicopathological variables and outcome in BC. However, this association is dependent on the molecular subtypes. Further functional assessment to detect its underlying mechanistic roles in BC subtypes is warranted.

Ki67 expression in invasive breast cancer: the use of tissue microarrays compared with whole tissue sections.

BACKGROUND: Although the prognostic value of Ki67 in breast cancer is well documented, using optimal cut-points for patient stratification, reproducibility of the scoring and interpretation of the results remains a matter of debate particularly when using tissue microarrays (TMAs). This study aims to assess Ki67 expression assessed on TMAs and their matched whole tissue sections (WTS). Moreover, whether the cut-off used for WTS is reproducible on TMA in BC molecular classes and the association between Ki67 expression cut-off, assessed on TMAs and WTS, and clinicopathological parameters and patient outcome were tested. METHOD: A large series (n = 707) of primary invasive breast tumours were immunostained for Ki67 using both TMA and WTS and assessed as percentage staining and correlated with each other, clinicopathological parameters and patient outcome. In addition, MKI67 mRNA expression was correlated with Ki67 protein levels on WTS and TMAs in a subset of cases included in the METABRIC study. RESULTS: There was moderate concordance in Ki67 expression between WTS and TMA when analysed as a continuous variable (Intraclass correlation coefficient = 0.61) and low concordance when dichotomised (kappa value = 0.3). TMA showed low levels of Ki67 with mean percentage of expression of 35 and 22% on WTS and TMA, respectively. MKI67 mRNA expression was significantly correlated with protein expression determined on WTS (Spearman Correlation, r = 0.52) and to a lesser extent on TMA (r = 0.34) (p < 0.001). Regarding prediction of patient outcome, statistically significant differences were detected upon stratification of patients with tumours expressing Ki67 at 10, 15, 20, 25 or 30% in TMA. Using TMA, ≥20% Ki67 provided the best prognostic cut-off particularly in triple-negative and HER2-positive classes. CONCLUSION: Ki67 expression in breast cancer can be evaluated using TMA although different cut-points are required to emulate results from WTS. A cut-off of ≥20% for Ki67 expression in BC provides the best prognostic correlations when TMAs are used.

Further evidence to support bimodality of oestrogen receptor expression in breast cancer.

AIMS: Although oestrogen receptor (ER)-negative breast cancers (BCs) do not respond to hormone therapy, the response of ER-positive BCs is reported to be variable, which may suggest a dose-dependent effect. The aim of this study was to assess the pattern of ER expression in BCs at the protein (immunohistochemistry) and transcriptome (microarray-based gene expression) levels. METHODS AND RESULTS: ER immunohistochemical (IHC) expression was assessed in a large series of BCs, including 3649 core biopsies and 1892 cases prepared as tissue microarrays (TMAs) stained with specific antibodies. ESR1 mRNA expression was assessed in the METABRIC study (1980 cases), by the use of the Linear Models for Microarray Data (limma) software, and the results were compared with protein levels. IHC data confirmed the bimodality of ER expression, with 92.2% and 89.2% of the cases showing completely negative (<1%) or highly positive (≥70%) expression on the cores and TMAs, respectively. Weakly positive cases (1-10%) and intermediately positive (11-69%) cases were infrequent (2.7% and 5.1%, and 1.6% and 9.2%, in cores and TMAs, respectively), and did not show survival difference from ER-negative tumours. When full-face sections of the corresponding excision specimens were immunostained, 47% of the ER-low/intermediate group were deemed to be ER-negative. Transcriptomic data not only showed a significant correlation between ESR1 mRNA and protein expression levels, but also confirmed the bimodality of ER expression at the mRNA level. CONCLUSIONS: Our study provides further evidence that ER expression is bimodal, and that it is observed at both the mRNA and protein levels. The reported poor survival of BC patients with low ER expression in the early clinical trials may be related to the inclusion of ER-negative cases.

Bimodality of intratumor Ki67 expression is an independent prognostic factor of overall survival in patients with invasive breast carcinoma.

Proliferative activity, assessed by Ki67 immunohistochemistry (IHC), is an established prognostic and predictive biomarker of breast cancer (BC). However, it remains under-utilized due to lack of standardized robust measurement methodologies and significant intratumor heterogeneity of expression. A recently proposed methodology for IHC biomarker assessment in whole slide images (WSI), based on systematic subsampling of tissue information extracted by digital image analysis (DIA) into hexagonal tiling arrays, enables computation of a comprehensive set of Ki67 indicators, including intratumor variability. In this study, the tiling methodology was applied to assess Ki67 expression in WSI of 152 surgically removed Ki67-stained (on full-face sections) BC specimens and to test which, if any, Ki67 indicators can predict overall survival (OS). Visual Ki67 IHC estimates and conventional clinico-pathologic parameters were also included in the study. Analysis revealed linearly independent intrinsic factors of the Ki67 IHC variance: proliferation (level of expression), disordered texture (entropy), tumor size and Nottingham Prognostic Index, bimodality, and correlation. All visual and DIA-generated indicators of the level of Ki67 expression provided significant cutoff values as single predictors of OS. However, only bimodality indicators (Ashman's D, in particular) were independent predictors of OS in the context of hormone receptor and HER2 status. From this, we conclude that spatial heterogeneity of proliferative tumor activity, measured by DIA of Ki67 IHC expression and analyzed by the hexagonal tiling approach, can serve as an independent prognostic indicator of OS in BC patients that outperforms the prognostic power of the level of proliferative activity.

Clinical utility of reverse phase protein array for molecular classification of breast cancer.

Reverse Phase Protein Array (RPPA) represents a sensitive and high-throughput technique allowing simultaneous quantitation of protein expression levels in biological samples. This study aimed to confirm the ability of RPPA to classify archival formalin-fixed paraffin-embedded (FFPE) breast cancer tissues into molecular classes used in the Nottingham prognostic index plus (NPI+) determined by immunohistochemistry (IHC). Proteins were extracted from FFPE breast cancer tissues using three extraction protocols: the Q-proteome FFPE Tissue Kit (Qiagen, Hilden, Germany) and two in-house methods using Laemmli buffer with either incubation for 20 min or 2 h at 105 °C. Two preparation methods, full-face sections and macrodissection, were used to assess the yield and quality of protein extracts. Ten biomarkers used for the NPI+ (ER, PgR, HER2, Cytokeratins 5/6 and 7/8, EGFR, HER3, HER4, p53 and Mucin 1) were quantified using RPPA and compared to results determined by IHC. The Q-proteome FFPE Tissue Kit produced significantly higher protein concentration and signal intensities. The intra- and inter-array reproducibility assessment indicated that RPPA using FFPE lysates was a highly reproducible and robust technique. Expression of the biomarkers individually and in combination using RPPA was highly consistent with IHC results. Macrodissection of the invasive tumour component gave more reliable results with the majority of biomarkers determined by IHC, (80 % concordance) compared with full-face sections (60 % concordance). Our results provide evidence for the technical feasibility of RPPA for high-throughput protein expression profiling of FFPE breast cancer tissues. The sensitivity of the technique is related to the quality of extracted protein and purity of tumour tissue. RPPA could provide a quantitative technique alternative to IHC for the biomarkers used in the NPI+.

Prognostic and biological significance of peroxisome proliferator-activated receptor-gamma in luminal breast cancer.

Peroxisome proliferator-activated receptor-gamma (PPARγ) is an adopted orphan receptor that belongs to the nuclear receptor superfamily of transcription factors. PPARγ is regarded as a differentiation factor and it plays an important role in regulating adipogenesis, cell growth, proliferation and tumour progression. In breast cancer (BC), PPARγ agonists were reported to inhibit proliferation and growth invasion and promote phenotypic changes associated with a less malignant and more differentiated status. This study aims to assess the prognostic and biological roles of PPARγ protein expression in a large cohort of BC patients (n = 1100) with emphasis on the luminal oestrogen receptor (ER) positive class. Immunohistochemistry was used to assess the levels of PPARγ expression in BC series prepared as tissue microarrays (TMAs). PPARγ antibody specificity was confirmed using Western blotting. PPARγ nuclear expression was detected in 79 % of the cases and its expression was positively correlated with the hormonal receptors (ER, progesterone receptor and androgen receptor). PPARγ levels were significantly higher in tumours with lobular subtype, smaller size and lower grade, while HER2-positive, ductal or medullary tumours were associated with lower PPARγ levels. Survival analysis showed that PPARγ is associated with better outcome in the whole series as well as in luminal ER-positive class. Cox regression model showed that PPARγ is an independent predictor of outcome. Higher PPARγ was associated with longer survival in patients with ER-positive tumours who did not receive hormone therapy. PPARγ is a good prognostic marker associated with hormone receptors. In patients with luminal BCs, PPARγ is a marker of better prognosis and is associated with longer survival.