Cyclin A as a marker for prognosis and chemotherapy response in advanced breast cancer

We wanted to study cyclin A as a marker for prognosis and chemotherapy response. A total of 283 women with metastatic breast cancer were initially enrolled in a randomised multicentre trial comparing docetaxel to sequential methotrexate-fluorouracil (MF) in advanced breast cancer after anthracycline failure. Paraffin-embedded blocks of the primary tumour were available for 96 patients (34%). The proportion of cells expressing cyclin A was determined by immunohistochemistry using a mouse monoclonal antibody to human cyclin A. Response evaluation was performed according to WHO recommendations. The median cyclin A positivity of tumour cells was 14.5% (range 1.2–45.0). Cyclin A correlated statistically significantly to all other tested proliferation markers (mitotic count, histological grade and Ki-67). A high cyclin A correlated significantly to a shorter time to first relapse, risk ratio (RR) 1.94 (95% CI 1.24–3.03) and survival from diagnosis, RR 2.49 (95% CI 1.45–4.29), cutoff point for high/low proliferation group 10.5%. Cyclin A did not correlate to chemotherapy response or survival after anthracycline, docetaxel or MF therapy. Of all tumour biological factors tested (mitotic count, histological grade and Ki-67), cyclin A seemed to have the strongest prognostic value. Cyclin A is a good marker for tumour proliferation and prognosis in breast cancer. In the present study, cyclin A did not predict chemotherapy response

Reliability of cyclin A assessment on tissue microarrays in breast cancer compared to conventional histological slides

Cyclin A has in some studies been associated with poor breast cancer survival, although all studies have not confirmed this. Its prognostic significance in breast cancer needs evaluation in larger studies. Tissue microarray (TMA) technique allows a simultaneous analysis of large amount of tumours on a single microscopic slide. This makes a rapid screening of molecular markers in large amount of tumours possible. Because only a small tissue sample of each tumour is punched on an array, the question has arisen about the representativeness of TMA when studying markers that are expressed in only a small proportion of cells. For this reason, we wanted to compare cyclin A expression on TMA and on traditional large sections. Two breast cancer TMAs were constructed of 200 breast tumours diagnosed between 1997–1998. TMA slides and traditional large section slides of these 200 tumours were stained with cyclin A antibody and analysed by two independent readers. The reproducibility of the two readers' results was good or even very good, with kappa values 0.71–0.87. The agreement of TMA and large section results was good with kappa value 0.62–0.75. Cyclin A overexpression was significantly (P<0.001) associated with oestrogen receptor and progesterone receptor negativity and high grade both on TMA and large sections. Cyclin A overexpression was significantly associated with poor metastasis-free survival both on TMA and large sections. The relative risks for metastasis were similar on TMA and large sections. This study suggests that TMA technique could be useful to study histological correlations and prognostic significance of cyclin A on breast cancer on a large scale

Genomic instability and proliferative activity as risk factors for distant metastases in breast cancer

The role of genomic instability and proliferative activity for development of distant metastases in breast cancer was analysed, and the relative contribution of these two risk factors was quantified. A detailed quantitative comparison was performed between Ki67 and cyclin A as proliferative markers. The frequency of Ki67 and cyclin A-positive cells was scored in the same microscopic areas in 428 breast tumours. The frequency of Ki67-positive cells was found to be highly correlated with the frequency of cyclin A-positive cells, and both proliferation markers were equally good to predict risk of distant metastases. The relative contribution of degree of aneuploidy and proliferative activity as risk markers for developing distant metastases was studied independently. Although increased proliferative activity in general was associated with an increased risk of developing distant metastases, ploidy level was found to be an independent and even stronger marker when considering the group of small (T1) node negative tumours. By combining proliferative activity and ploidy level, a large group of low risk breast tumours (39%) could be identified in which only a few percentage of the tumours (5%) developed distant metastases during the 9-year follow-up time period

Identification of a gene signature in cell cycle pathway for breast cancer prognosis using gene expression profiling data

<p>Abstract</p> <p>Background</p> <p>Numerous studies have used microarrays to identify gene signatures for predicting cancer patient clinical outcome and responses to chemotherapy. However, the potential impact of gene expression profiling in cancer diagnosis, prognosis and development of personalized treatment may not be fully exploited due to the lack of consensus gene signatures and poor understanding of the underlying molecular mechanisms.</p> <p>Methods</p> <p>We developed a novel approach to derive gene signatures for breast cancer prognosis in the context of known biological pathways. Using unsupervised methods, cancer patients were separated into distinct groups based on gene expression patterns in one of the following pathways: apoptosis, cell cycle, angiogenesis, metastasis, p53, DNA repair, and several receptor-mediated signaling pathways including chemokines, EGF, FGF, HIF, MAP kinase, JAK and NF-κB. The survival probabilities were then compared between the patient groups to determine if differential gene expression in a specific pathway is correlated with differential survival.</p> <p>Results</p> <p>Our results revealed expression of cell cycle genes is strongly predictive of breast cancer outcomes. We further confirmed this observation by building a cell cycle gene signature model using supervised methods. Validated in multiple independent datasets, the cell cycle gene signature is a more accurate predictor for breast cancer clinical outcome than the previously identified Amsterdam 70-gene signature that has been developed into a FDA approved clinical test MammaPrint^®.</p> <p>Conclusion</p> <p>Taken together, the gene expression signature model we developed from well defined pathways is not only a consistently powerful prognosticator but also mechanistically linked to cancer biology. Our approach provides an alternative to the current methodology of identifying gene expression markers for cancer prognosis and drug responses using the whole genome gene expression data.</p

Measuring proliferation in breast cancer: practicalities and applications

Various methods are available for the measurement of proliferation rates in tumours, including mitotic counts, estimation of the fraction of cells in S-phase of the cell cycle and immunohistochemistry of proliferation-associated antigens. The evidence, advantages and disadvantages for each of these methods along with other novel approaches is reviewed in relation to breast cancer. The potential clinical applications of proliferative indices are discussed, including their use as prognostic indicators and predictors of response to systemic therapy

Estimating the Prevalence and Cost of Yield-Switching Fraud in the Federal Crop Insurance Program

Producers who manipulate and switch their reported crop-yields between separately insured units can increase their insurance indemnities substantially. A statistical model that identifies potential yield switching is developed. The unrestricted statistical model is singular and is identified by imposing a mixture of system-estimable and system-nonestimable restrictions. Lower bound estimates of yield-switching fraud incidence and costs are obtained by applying the model to 207,067 multiple unit producers who purchased crop insurance in 1998. Copyright 2006, Oxford University Press.