Predicting a local recurrence after breast-conserving therapy by gene expression profiling

Introduction

To tailor local treatment in breast cancer patients there is a need for predicting ipsilateral recurrences after breast-conserving therapy. After adequate treatment (excision with free margins and radiotherapy), young age and incompletely excised extensive intraductal component are predictors for local recurrence, but many local recurrences can still not be predicted. Here we have used gene expression profiling by microarray analysis to identify gene expression profiles that can help to predict local recurrence in individual patients.

Methods

By using previously established gene expression profiles with proven value in predicting metastasis-free and overall survival (wound-response signature, 70-gene prognosis profile and hypoxia-induced profile) and training towards an optimal prediction of local recurrences in a training series, we establish a classifier for local recurrence after breast-conserving therapy.

Results

Validation of the different gene lists shows that the wound-response signature is able to separate patients with a high (29%) or low (5%) risk of a local recurrence at 10 years (sensitivity 87.5%, specificity 75%). In multivariable analysis the classifier is an independent predictor for local recurrence.

Conclusion

Our findings indicate that gene expression profiling can identify subgroups of patients at increased risk of developing a local recurrence after breast-conserving therapy.

Prognostic value of morphometry and DNA flow-cytometry features of invasive breast cancers detected by population screening: comparison with control group of hospital patients

Using the prognostic value of morphometric and flow-cytometric features, a group of patients with invasive breast cancers detected with population screening (PS, n = 70) has been evaluated and compared with a random control group in 2 hospitals (H group, n = 225) diagnosed in the same period. The results show that the PS patients had smaller tumors, less positive lymph nodes, better differentiated tumors with a lower mitotic activity index (MAI) and lower values of the morphometric prognostic index (MPI). Furthermore, the women more frequently had diploid tumors and tumors with small nuclei. The second purpose was to evaluate whether quantitative microscopical features, in comparison with other prognostic features such as size of primary tumor, nodal status and histologic grade, are as strong prognosticators in PS tumors as in H-detected breast cancers. In comparison with H tumors, morphometric and flow-cytometric features, as well as tumor size, had the same prognostic value for the PS tumors. In contrast, nodal status was not significant within the PS group, and the same phenomenon was found in a subgroup of H patients with similar sized tumors. Of all quantitative microscopical features (MPI, MAI, mean nuclear area (MNA) and DNA Index (DI], the MAI had the strongest prognostic value. DI showed additional prognostic value to the MAI for patients with small tumors and with small tumor-cell nuclei, because a diploid pattern in these cases (this combination occurred in 21 patients of the total group = 30%) was correlated with a 95% 10-year survival rate. Histologic grade, although significant within the large H group, was of no prognostic value within the PS group, and also not as in the H sub-group with small tumors. It is concluded from morphometric and DNA flow-cytometric criteria that these prognostic features in invasive breast cancers detected by PS were all more favorable than in randomly detected hospital breast cancers. This may account for the reported better survival rate of PS patients. Furthermore, the prognosis of patients with small invasive breast cancers detected by population screening can be more accurately deduced by quantitative microscopical features than by axillary-lymph-node status.