Background:Breast cancer is heterogeneous and the existing prognostic classifiers are limited in accuracy, leading to unnecessary treatment of numerous women. B-cell lymphoma 2 (BCL2), an antiapoptotic protein, has been proposed as a prognostic marker, but this effect is considered to relate to oestrogen receptor (ER) status. This study aimed to test the clinical validity of BCL2 as an independent prognostic marker.Methods:Five studies of 11 212 women with early-stage breast cancer were analysed. Individual patient data included tumour size, grade, lymph node status, endocrine therapy, chemotherapy and mortality. BCL2, ER, progesterone receptor (PR) and human epidermal growth factor receptor 2 (HER2) levels were determined in all tumours. A Cox model incorporating the time-dependent effects of each variable was used to explore the prognostic significance of BCL2.Results:In univariate analysis, ER, PR and BCL2 positivity was associated with improved survival and HER2 positivity with inferior survival. For ER and PR this effect was time dependent, whereas for BCL2 and HER2 the effect persisted over time. In multivariate analysis, BCL2 positivity retained independent prognostic significance (hazard ratio (HR) 0.76, 95% confidence interval (CI) 0.66–0.88, P<0.001). BCL2 was a powerful prognostic marker in ER− (HR 0.63, 95% CI 0.54–0.74, P<0.001) and ER+ disease (HR 0.56, 95% CI 0.48–0.65, P<0.001), and in HER2− (HR 0.55, 95% CI 0.49–0.61, P<0.001) and HER2+ disease (HR 0.70, 95% CI 0.57–0.85, P<0.001), irrespective of the type of adjuvant therapy received. Addition of BCL2 to the Adjuvant! Online prognostic model, for a subset of cases with a 10-year follow-up, improved the survival prediction (P=0.0039).Conclusions:BCL2 is an independent indicator of favourable prognosis for all types of early-stage breast cancer. This study establishes the rationale for introduction of BCL2 immunohistochemistry to improve prognostic stratification. Further work is now needed to ascertain the exact way to apply BCL2 testing for risk stratification and to standardise BCL2 immunohistochemistry for this application.

Purpose: Prognostication of breast cancer using clinicopathologic variables, although useful, remains imperfect. Many reports suggest that gene expression profiling can refine the current approach. Alternatively, it has been shown that panels of proteins assessed by immunohistochemistry might also be useful in this regard.We evaluate the prognostic potential of a panel of markers by immunohistochemistry in a large case series to establish if either a single marker or a panel could improve the prognostic power of the Nottingham Prognostic Index (NPI).We validated the results in an independent series. Experimental Design and Results: The expression of 13 biomarkers was evaluated in 930 breast cancers on a tissue microarray. Eight markers [estrogen receptor (ER), progesterone receptor (PR), Bcl-2, cyclin E, p53, MIB-1, cytokeratin 5/6, and HER2] showed a significant association with survival at 10 years on univariate analysis. On multivariate analysis that included these eight markers and the NPI, only the NPI [hazard ratio (HR), 1.35; 95% confidence interval (95 % CI), 1.16-1.56; P = 0.0005], ER (HR, 0.59; 95 % CI, 0.39-0.88; P = 0.011), and Bcl-2 (HR, 0.68; 95% CI, 0.46-0.99; P = 0.055) were significant. In a subsequent multivariate analysis that included the NPI, ER, and Bcl-2, only Bcl-2 (HR, 0.62; 95% CI, 0.44-0.87; P = 0.006) remained independent of NPI (HR, 1.50; 95% CI, 1.16-1.56; P = 0.004). In addition, Bcl-2, used as a single marker, was more powerful than the use of a panel of markers. Based on these results, an independent series was used to validate the prognostic significance of Bcl-2. ER and PR were also evaluated in this validation series. Bcl-2 (HR, 0.83; 95% CI, 0.71-0.96; P = 0.018) retained prognostic significance independent of the NPI (HR, 2.04; 95% CI, 1.67-2.51; P < 0.001) with an effect that was maximal in the first 5 years. Conclusion:Bcl-2 is an independent predictor of breast cancer outcome and seems to be useful as a prognostic adjunct to the NPI, particularly in the first 5 years after diagnosis.

Background: A number of protein markers have been investigated as prognostic adjuncts in breast cancer but their translation into clinical practice has been impeded by a lack of appropriate validation. Recently, we showed that BCL2 protein expression had prognostic power independent of current used standards. Here, we present the results of a meta-analysis of the association between BCL2 expression and both disease free survival (DFS) and overall survival (OS) in female breast cancer.

Mcm-2 may be of utility as a prognostic marker to refine the prediction of outcome in breast cancer, for example when combined with parameters currently used in the NPI.

The histopathologic classification of breast cancer stratifies tumors based on tumor grade, stage, and type. Despite an overall correlation with survival, this classification is poorly predictive and tumors with identical grade and stage can have markedly contrasting outcomes. Recently, breast carcinomas have been classified by their gene expression profiles on frozen material. The validation of such a classification on formalin-fixed paraffin-embedded tumor archives linked to clinical information in a high-throughput fashion would have a major impact on clinical practice. The authors tested the ability of tumor tissue microarrays (TMAs) to sub-classify breast cancers using a TMA containing 107 breast cancers. The pattern of expression of 13 different protein biomarkers was assessed by immunohistochemistry and the multidimensional data was analyzed using an unsupervised two-dimensional clustering algorithm. This revealed distinct tumor clusters which divided into two main groups correlating with tumor grade (P<0.001) and nodal status (P = 0.04). None of the protein biomarkers tested could individually identify these groups. The biological significance of this classification is supported by its similarity with one derived from gene expression microarray analysis. Thus, molecular profiling of breast cancer using a limited number of protein biomarkers in TMAs can sub-classify tumors into clinically and biologically relevant subgroups.

Geminin inhibits DNA replication by preventing Cdt1 from loading minichromosome maintenance (MCM) proteins onto DNA. The present study has investigated whether the frequency of geminin expression predicts clinical outcome in breast cancer. Immunohistochemistry was used first to examine geminin expression in normal and malignant breast tissue (n = 67). Correlations with cell-cycle parameters, pathological features, and clinical outcome were then determined using an invasive breast carcinoma tissue microarray (n = 165). Breast carcinomas were scanned for mutations (n = 61) and copy number imbalances (n = 241) of the geminin gene. Finally, the cell cycle distribution of geminin in breast cancer cells was investigated in vivo and in vitro. Despite a putative tumour suppressor function, it was found that increased geminin expression is a powerful independent indicator of adverse prognosis in invasive breast cancer. Both poor overall survival (p = 0.0002) and the development of distant metastases (p = 0.005) are predicted by high geminin expression, which performs better in this patient cohort than traditional factors currently used to determine prognosis and appropriate therapy. No mutations or deletions of the geminin gene and no evidence that a high frequency of protein expression is related to gene amplification were found. It is shown that geminin is expressed from S to M phase in breast carcinoma tissue and cell lines, disappearing at the metaphase--anaphase transition. While MCM proteins identify all non-quiescent cells, geminin identifies the sub-fraction that have entered S phase, but not exited mitosis, thereby indicating the rate of cell-cycle progression. It is suggested that this explains its unexpected value as a prognostic marker in breast cancer.

Most studies of genomic rearrangements in common cancers have focused on regional gains and losses, but some rearrangements may break within specific genes. We previously reported that five breast cancer cell lines have chromosome translocations that break in the NRG1 gene and that could cause abnormal NRG1 expression. NRG1 encodes the Neuregulins 1 (formerly the Heregulins), ligands for members of the ErbB/epidermal growth factor-receptor family, which includes ErbB2/HER2. We have now screened for breaks at NRG1 in paraffin sections of breast tumors. Tissue microarrays were screened by fluorescence in situ hybridization, with hybridization probes proximal and distal to the expected breakpoints. This screen detects breaks but does not distinguish between translocation or deletion breakpoints. The screen was validated with arraycomparative genomic hybridization on a custom 8p12 high-density genomic array to detect a lower copy number of the sequences that were lost distal to the breaks. We also precisely mapped the breaks in five tumors with different hybridization probes. Breaks in NRG1 were detected in 6% (19 of 323) of breast cancers and in some lung and ovarian cancers. In an unselected series of 213 cases with follow-up, breast cancers where the break was detected tended to be high-grade (65% grade III compared with 28% of negative cases). They were, like breast tumors in general, mainly ErbB2 low (11 of 13 were low) and estrogen receptor positive (11 of 13 positive).

To identify markers of non-response to neoadjuvant chemotherapy (NAC) that could be used in the adjuvant setting. Sixteen pathologists of the European Working Group for Breast Screening Pathology reviewed the core biopsies of breast cancers treated with NAC and recorded the clinico-pathological findings (histological type and grade; estrogen, progesterone receptors, and HER2 status; Ki67; mitotic count; tumor-infiltrating lymphocytes; necrosis) and data regarding the pathological response in corresponding surgical resection specimens. Analyses were carried out in a cohort of 490 cases by comparing the groups of patients showing pathological complete response (pCR) and partial response (pPR) with the group of non-responders (pathological non-response: pNR). Among other parameters, the lobular histotype and the absence of inflammation were significantly more common in pNR (p < 0.001). By ROC curve analyses, cut-off values of 9 mitosis/2 mm2 and 18 % of Ki67-positive cells best discriminated the pNR and pCR + pPR categories (p = 0.018 and < 0.001, respectively). By multivariable analysis, only the cut-off value of 9 mitosis discriminated the different response categories (p = 0.036) in the entire cohort. In the Luminal B/HER2− subgroup, a mitotic count <9, although not statistically significant, showed an OR of 2.7 of pNR. A lobular histotype and the absence of inflammation were independent predictors of pNR (p = 0.024 and <0.001, respectively). Classical morphological parameters, such as lobular histotype and inflammation, confirmed their predictive value in response to NAC, particularly in the Luminal B/HER2− subgroup, which is a challenging breast cancer subtype from a therapeutic point of view. Mitotic count could represent an additional marker but has a poor positive predictive value.Electronic supplementary materialThe online version of this article (doi:10.1007/s10549-014-3192-3) contains supplementary material, which is available to authorized users.