Comments on the use of a single or multiple probeset approach for microarray-based analyses of routine molecular markers in breast cancer

BIRC5 (survivin): a pejorative prognostic marker in stage II/III breast cancer with no response to neoadjuvant chemotherapy

PURPOSE

Neoadjuvant systemic therapy (NAC) is currently used in the treatment of stage II/III breast cancer. Pathological complete response as a surrogate endpoint for clinical outcomes is not completely validated for all subgroups of breast cancers. Therefore, there is a need for reliable predictive tests of the most effective treatment.

METHODS

We used a combination of predictive clinical, pathological, and gene expression-based markers of response to NAC in a prospective phase II multicentre randomized clinical trial in breast cancer patients, with a long follow-up (8 years). This study concerned the subpopulation of 188 patients with similar levels of pathological response rates to sequential epirubicin/cyclophosphamide and docetaxel to determine predictive marker of pCR and DFS. We used a set of 45 genes selected from high throughput analysis and a standardized RT-qPCR. We analyzed the predictive markers of pathological complete response (pCR) and DFS in the overall population and DFS the subpopulation of 159 patients with no pCR.

RESULTS

In the overall population, combining both clinical and genomic variables, large tumor size, low TFF1, and MYBL2 overexpression were significantly associated with pCR. T4 Stage, lymphovascular invasion, negative PR status, histological type, and high values of CCNB1 were associated with DFS. In the no pCR population, only lymphovascular invasion and high values of BIRC5 were associated with DFS.

CONCLUSIONS

We confirm the importance of ER-related and proliferation genes in the prediction of pCR in NAC-treated breast cancer patients. Furthermore, we identified BIRC5 (survivin) as a main pejorative prognostic factor in patients with breast cancers with no pCR. These results also open perspective for predictive markers of new targeted therapies.

Challenging single- and multi-probesets gene expression signatures of pathological complete response to neoadjuvant chemotherapy in breast cancer: experience of the REMAGUS 02 phase II trial

This study was designed to identify predictive signatures of pathological complete response (pCR) in breast cancer treated by taxane-based regimen, using clinicopathological variables and transcriptomic data (Affymetrix Hgu133 Plus 2.0 devices). The REMAGUS 02 trial (n = 153,training set) and the publicly available M.D. Anderson data set (n = 133, validation set) were used. A re-sampling method was applied. All predictive models were defined using logistic regression and their classification performances were tested through Area Under the Curve (AUC) estimation. A stable set of 42 probesets (31 genes) differentiate pCR or no pCR samples. Single-or 2-probesets signatures, mainly related to ER pathway, were equally predictive of pCR with AUC greater then 0.80. Models including probesets associated with ESR1, MAPT, CA12 or PIGH presented good classification performances. When clinical variables were entered into the model, only CA12 and PIGH, remained informative (p = 0.05 and p = 0.005) showing that a combination of a few genes provided robust and reliable prediction of pCR.