Valerie Speirs

Choosing the right cell line for breast cancer research

Breast cancer is a complex and heterogeneous disease. Gene expression profiling has contributed significantly to our understanding of this heterogeneity at a molecular level, refining taxonomy based on simple measures such as histological type, tumour grade, lymph node status and the presence of predictive markers like oestrogen receptor and human epidermal growth factor receptor 2 (HER2) to a more sophisticated classification comprising luminal A, luminal B, basal-like, HER2-positive and normal subgroups. In the laboratory, breast cancer is often modelled using established cell lines. In the present review we discuss some of the issues surrounding the use of breast cancer cell lines as experimental models, in light of these revised clinical classifications, and put forward suggestions for improving their use in translational breast cancer research.

Critical research gaps and translational priorities for the successful prevention and treatment of breast cancer

IntroductionBreast cancer remains a significant scientific, clinical and societal challenge. This gap analysis has reviewed and critically assessed enduring issues and new challenges emerging from recent research, and proposes strategies for translating solutions into practice.MethodsMore than 100 internationally recognised specialist breast cancer scientists, clinicians and healthcare professionals collaborated to address nine thematic areas: genetics, epigenetics and epidemiology; molecular pathology and cell biology; hormonal influences and endocrine therapy; imaging, detection and screening; current/novel therapies and biomarkers; drug resistance; metastasis, angiogenesis, circulating tumour cells, cancer ‘stem’ cells; risk and prevention; living with and managing breast cancer and its treatment. The groups developed summary papers through an iterative process which, following further appraisal from experts and patients, were melded into this summary account.ResultsThe 10 major gaps identified were: (1) understanding the functions and contextual interactions of genetic and epigenetic changes in normal breast development and during malignant transformation; (2) how to implement sustainable lifestyle changes (diet, exercise and weight) and chemopreventive strategies; (3) the need for tailored screening approaches including clinically actionable tests; (4) enhancing knowledge of molecular drivers behind breast cancer subtypes, progression and metastasis; (5) understanding the molecular mechanisms of tumour heterogeneity, dormancy, de novo or acquired resistance and how to target key nodes in these dynamic processes; (6) developing validated markers for chemosensitivity and radiosensitivity; (7) understanding the optimal duration, sequencing and rational combinations of treatment for improved personalised therapy; (8) validating multimodality imaging biomarkers for minimally invasive diagnosis and monitoring of responses in primary and metastatic disease; (9) developing interventions and support to improve the survivorship experience; (10) a continuing need for clinical material for translational research derived from normal breast, blood, primary, relapsed, metastatic and drug-resistant cancers with expert bioinformatics support to maximise its utility. The proposed infrastructural enablers include enhanced resources to support clinically relevant in vitro and in vivo tumour models; improved access to appropriate, fully annotated clinical samples; extended biomarker discovery, validation and standardisation; and facilitated cross-discipline working.ConclusionsWith resources to conduct further high-quality targeted research focusing on the gaps identified, increased knowledge translating into improved clinical care should be achievable within five years.

Comparison of microfluidic digital PCR and conventional quantitative PCR for measuring copy number variation

One of the benefits of Digital PCR (dPCR) is the potential for unparalleled precision enabling smaller fold change measurements. An example of an assessment that could benefit from such improved precision is the measurement of tumour-associated copy number variation (CNV) in the cell free DNA (cfDNA) fraction of patient blood plasma. To investigate the potential precision of dPCR and compare it with the established technique of quantitative PCR (qPCR), we used breast cancer cell lines to investigate HER2 gene amplification and modelled a range of different CNVs. We showed that, with equal experimental replication, dPCR could measure a smaller CNV than qPCR. As dPCR precision is directly dependent upon both the number of replicate measurements and the template concentration, we also developed a method to assist the design of dPCR experiments for measuring CNV. Using an existing model (based on Poisson and binomial distributions) to derive an expression for the variance inherent in dPCR, we produced a power calculation to define the experimental size required to reliably detect a given fold change at a given template concentration. This work will facilitate any future translation of dPCR to key diagnostic applications, such as cancer diagnostics and analysis of cfDNA.

Reduced expression of oestrogen receptor β in invasive breast cancer and its re-expression using DNA methyl transferase inhibitors in a cell line model

To gain insights into the possible role of oestrogen receptor (ER) β in breast carcinogenesis, immunohistochemical analysis of ER β was performed on 512 breast specimens encompassing normal (n = 138), pure ductal carcinoma in situ (n = 16), invasive cancers (n = 319), lymph node metastases (n = 31), and recurrences (n = 8). Real‐time polymerase chain reaction (PCR) was used to investigate the methylation status of the ER β gene in the ER β negative breast cancer cell lines SkBr3 and MDA‐MB‐435. A gradual reduction in, but not a complete loss of, ER β expression was observed during the transition from normal and pre‐invasive lesions to invasive cancers, where ER β was lost in 21% of cases. This was more pronounced in invasive ductal than in lobular carcinomas, a significantly higher proportion of which were ER β‐positive (74% compared with 91%, respectively, p = 0.0004). Examination of paired primary cancers with their axillary lymph node metastases showed that if ER β was present in the primary tumour, it persisted in the metastasis. Treatment of ER β‐negative cell lines with DNA methyl transferase inhibitors restored ER β expression, providing experimental evidence that silencing of ER β in breast carcinomas could be due to promoter hypermethylation. These results suggest that loss of ER β expression is one of the hallmarks of breast carcinogenesis and that it may be a reversible process involving methylation. Copyright

Phyto-oestrogens and breast cancer chemoprevention

Phytoestrogens are polyphenol compounds of plant origin that exhibit a structural similarity to the mammalian steroid hormone 17β-oestradiol. In Asian nations the staple consumption of phyto-oestrogen-rich foodstuffs correlates with a reduced incidence of breast cancer. Human dietary intervention trials have noted a direct relationship between phyto-oestrogen ingestion and a favourable hormonal profile associated with decreased breast cancer risk. However, these studies failed to ascertain the precise effect of dietary phyto-oestrogens on the proliferation of mammary tissue. Epidemiological and rodent studies crucially suggest that breast cancer chemoprevention by dietary phyto-oestrogen compounds is dependent on ingestion before puberty, when the mammary gland is relatively immature. Phyto-oestrogen supplements are commercially marketed for use by postmenopausal women as natural and safe alternatives to hormone replacement therapy. Of current concern is the effect of phyto-oestrogen compounds on the growth of pre-existing breast tumours. Data are contradictory, with cell culture studies reporting both the oestrogenic stimulation of oestrogen receptor-positive breast cancer cell lines and the antagonism of tamoxifen activity at physiological phyto-oestrogen concentrations. Conversely, phyto-oestrogen ingestion by rodents is associated with the development of less aggressive breast tumours with reduced metastatic potential. Despite the present ambiguity, current data do suggest a potential benefit from use of phyto-oestrogens in breast cancer chemoprevention and therapy. These aspects are discussed.

Nuclear and Cytoplasmic Expression of ERβ1, ERβ2, and ERβ5 Identifies Distinct Prognostic Outcome for Breast Cancer Patients

Purpose: Previous conflicting results about the prognostic significance of estrogen receptor (ER)-β in breast cancer may be explained by contribution of isoforms, of which five exist. Our aim was to elucidate the prognostic significance of ERβ1, ERβ2, and ERβ5 by immunohistochemistry in a large cohort of breast carcinomas with long-term follow-up. Experimental Design: Tissue microarrays were stained with ERβ1, ERβ2, and ERβ5 antibodies and scored as percentage of positive tumor cells and using the Allred system. Nuclear and cytoplasmic staining was evaluated and correlated with histopathologic characteristics, overall survival (OS), and disease-free survival (DFS). Results: Nuclear ERβ2 and ERβ5, but not ERβ1, significantly correlated with OS (P = 0.006, P = 0.039, and P = 0.099, respectively), and ERβ2 additionally with DFS (P = 0.013). ERβ2 also predicted response to endocrine therapy (P = 0.036); correlated positively with ERα, progesterone receptor, androgen receptor, and BRCA1; and correlated inversely with metastasis and vascular invasion. Tumors coexpressing ERβ2 and ERα had better OS and DFS. Cytoplasmic ERβ2 expression, alone or combined with nuclear staining, predicted significantly worse OS. Notably, patients with only cytoplasmic ERβ2 expression had significantly worse outcome (P = 0.0014). Conclusions: This is the first study elucidating the prognostic role of ERβ1, ERβ2, and ERβ5 in a large breast cancer series. ERβ2 is a powerful prognostic indicator in breast cancer, but nuclear and cytoplasmic expression differentially affect outcome. Measuring these in clinical breast cancer could provide a more comprehensive picture of patient outcome, complementing ERα.

Evaluation of seven oestrogen receptor β antibodies for immunohistochemistry, western blotting, and flow cytometry in human breast tissue

Two oestrogen receptors, ERα and ERβ, exist. While much is known about ERα, the role of ERβ is still undefined, especially at the protein level. The aim of this study was to determine the utility of seven ERβ antibodies (14C8, 8D5, PAI313, PPG5/10, N19, 9.88, and D7N) raised against different domains of ERβ in three commonly used laboratory applications, namely immunohistochemistry, western blot, and flow cytometry, using human breast material. For immunohistochemical analysis of frozen material, PAI313 and D7N gave stronger and more specific signals than 14C8, 8D5, and PPG5/10. In paraffin sections, 14C8, closely followed by PPG5/10, gave by far the most superior nuclear immunoreactivity, compared with the other antibodies tested. In general, flow cytometry results mirrored the immunohistochemistry data for paraffin sections, with antibodies ranked 14C8>8D5≥PAI‐313>PPG5/10>D7N. For western blotting, 8D5 and D7N yielded the strongest and most consistent bands, with weaker bands seen with the others. It is concluded that ERβ protein can be detected using specific antibodies. However, there is considerable variation between the specificity and application of these antibodies, highlighting the fact that careful optimization is required when selecting an antibody for use in a particular laboratory technique. Copyright

Oestrogen receptor β: what it means for patients with breast cancer

Summary Oestrogen receptor (ER)α is a well established prognostic marker in breast cancer, and all patients who are ER α positive receive tamoxifen as adjuvant endocrine therapy. Although ERα predicts a favourable disease outcome, the usefulness of ERβ as a clinical prognostic marker remains to be defined. Here, we outline the history of both ERs and discuss the implications ERβ has to patients with breast cancer.

Immunohistochemical detection of ERβ in breast cancer: towards more detailed receptor profiling?

Oestrogen receptor (ER) is used routinely to predict endocrine responsiveness in patients with breast cancer. A second ER, ERβ has been described but its significance remains undefined; most studies have described mRNA levels rather than protein expression. Here, we demonstrate for the first time, immunohistochemical detection of ERβ in archival breast tumours.

Relationship of Extreme Chromosomal Instability with Long-term Survival in a Retrospective Analysis of Primary Breast Cancer

Background: Chromosomal instability (CIN) is thought to be associated with poor prognosis in solid tumors; however, evidence from preclinical and mouse tumor models suggest that CIN may paradoxically enhance or impair cancer cell fitness. Breast cancer prognostic expression signature sets, which reflect tumor CIN status, efficiently delineate outcome in estrogen receptor ER-positive breast cancer in contrast to ER-negative breast cancer, suggesting that the relationship of CIN with prognosis differs in these two breast cancer subtypes. Methods: Direct assessment of CIN requires single-cell analysis methods, such as centromeric FISH, aimed at determining the variation around the modal number of two or more chromosomes within individual tumor nuclei. Here, we document the frequency of tumor CIN by dual centromeric FISH analysis in a retrospective primary breast cancer cohort of 246 patients with survival outcome. Results: There was increased CIN and clonal heterogeneity in ER-negative compared with ER-positive breast cancer. Consistent with a negative impact of CIN on cellular fitness, extreme CIN in ER-negative breast cancer was an independent variable associated with improved long-term survival in multivariate analysis. In contrast, a linear relationship of increasing CIN with poorer prognosis in ER-positive breast cancer was observed, using three independent measures of CIN. Conclusions: The paradoxical relationship between extreme CIN and cancer outcome in the ER-negative cohorts may explain why prognostic expression signatures, reflecting tumor CIN status, fail to predict outcome in this subgroup. Impact: Assessment of tumor CIN status may support risk stratification in ER-negative breast cancer and requires prospective validation. Cancer Epidemiol Biomarkers Prev; 20(10); 2183–94. ©2011 AACR.