Purpose: Molecular classification of breast cancer has been proposed based on gene expression profiles of human tumors. Luminal, basal-like, normal-like, and erbB2+ subgroups were identified and were shown to have different prognoses. The goal of this research was to determine if these different molecular subtypes of breast cancer also respond differently to preoperative chemotherapy. Experimental Design: Fine needle aspirations of 82 breast cancers were obtained before starting preoperative paclitaxel followed by 5-fluorouracil, doxorubicin, and cyclophosphamide chemotherapy. Gene expression profiling was done with Affymetrix U133A microarrays and the previously reported ''breast intrinsic''gene set was used for hierarchical clustering and multidimensional scaling to assign molecular class. Results: The basal-like and erbB2+ subgroups were associated with the highest rates of pathologic complete response (CR), 45% [95% confidence interval (95% CI), 24-68] and 45% (95% CI, 23-68), respectively, whereas the luminal tumors had a pathologic CR rate of 6% (95% CI, 1-21). No pathologic CR was observed among the normal-like cancers (95% CI, 0-31). Molecular class was not independent of conventional cliniocopathologic predictors of response such as estrogen receptor status and nuclear grade. None of the 61genes associated with pathologic CR in the basal-like group were associated with pathologic CR in the erbB2+ group, suggesting that the molecular mechanisms of chemotherapy sensitivity may vary between these two estrogen receptor^negative subtypes. Conclusions: The basal-like and erbB2+ subtypes of breast cancer are more sensitive to paclitaxel-and doxorubicin-containing preoperative chemotherapy than the luminal and normallike cancers.Breast cancer is a clinically heterogeneous disease. Histologically similar tumors may have different prognoses and may respond to therapy differently. It is believed that these differences in clinical behavior are due to molecular differences between histologically similar tumors. DNA microarray technology is ideally suited to reveal such molecular differences. A novel molecular classification of breast cancer based on gene expression profiles was recently proposed (1). The investigators identified a set of stably expressed genes (''intrinsic gene set''; n = 534) that accounted for much of the molecular differences between 42 breast cancers and did hierarchical cluster analysis to identify subgroups of cancers with separate gene expression profiles. Luminal, basal-like, normal-like, and erbB2+ subgroups were identified and were shown to have different prognoses (1 -4). These results were confirmed in follow-up experiments by the same group and others using larger numbers of cases. The basal-like (mostly estrogen receptor negative) and erbB2+ (mostly HER-2 amplified and estrogen receptor negative) subgroups had the shortest relapse-free and overall survival, whereas the luminal-type (estrogen receptorpositive) tumors had a more favorable clinical outcome (2 -4).

RCB determined from routine pathologic materials represented the distribution of RD, was a significant predictor of DRFS, and can be used to define categories of near-complete response and chemotherapy resistance.

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Phosphatidylinositol 3-kinase (PI3K)/AKT pathway aberrations are common in cancer. By applying mass spectroscopybased sequencing and reverse-phase protein arrays to 547 human breast cancers and 41 cell lines, we determined the subtype specificity and signaling effects of PIK3CA, AKT, and PTEN mutations and the effects of PIK3CA mutations on responsiveness to PI3K inhibition in vitro and on outcome after adjuvant tamoxifen. PIK3CA mutations were more common in hormone receptor-positive (34.5%) and HER2-positive (22.7%) than in basal-like tumors (8.3%). AKT1 (1.4%) and PTEN (2.3%) mutations were restricted to hormone receptor-positive cancers. Unlike AKT1 mutations that were absent from cell lines, PIK3CA (39%) and PTEN (20%) mutations were more common in cell lines than tumors, suggesting a selection for these but not AKT1 mutations during adaptation to culture. PIK3CA mutations did not have a significant effect on outcome after adjuvant tamoxifen therapy in 157 hormone receptor-positive breast cancer patients. PIK3CA mutations, in comparison with PTEN loss and AKT1 mutations, were associated with significantly less and inconsistent activation of AKT and of downstream PI3K/AKT signaling in tumors and cell lines. PTEN loss and PIK3CA mutation were frequently concordant, suggesting different contributions to pathophysiology. PTEN loss rendered cells significantly more sensitive to growth inhibition by the PI3K inhibitor LY294002 than did PIK3CA mutations. Thus, PI3K pathway aberrations likely play a distinct role in the pathogenesis of different breast cancer subtypes. The specific aberration present may have implications for the selection of PI3K-targeted therapies in hormone receptor-positive breast cancer. [Cancer Res 2008;68(15):6084-91]

Some of the anti-neoplastic effects of anthracyclines in mice originate from the induction of innate and T cell-mediated anticancer immune responses. Here we demonstrate that anthracyclines stimulate the rapid production of type I interferons (IFNs) by malignant cells after activation of the endosomal pattern recognition receptor Toll-like receptor 3 (TLR3). By binding to IFN-α and IFN-β receptors (IFNARs) on neoplastic cells, type I IFNs trigger autocrine and paracrine circuitries that result in the release of chemokine (C-X-C motif) ligand 10 (CXCL10). Tumors lacking Tlr3 or Ifnar failed to respond to chemotherapy unless type I IFN or Cxcl10, respectively, was artificially supplied. Moreover, a type I IFN-related signature predicted clinical responses to anthracycline-based chemotherapy in several independent cohorts of patients with breast carcinoma characterized by poor prognosis. Our data suggest that anthracycline-mediated immune responses mimic those induced by viral pathogens. We surmise that such 'viral mimicry' constitutes a hallmark of successful chemotherapy.

Over the last decade, the introduction of microarray technology has had a profound impact on gene expression research. The publication of studies with dissimilar or altogether contradictory results, obtained using different microarray platforms to analyze identical RNA samples, has raised concerns about the reliability of this technology. The MicroArray Quality Control (MAQC) project was initiated to address these concerns, as well as other performance and data analysis issues. Expression data on four titration pools from two distinct reference RNA samples were generated at multiple test sites using a variety of microarray-based and alternative technology platforms. Here we describe the experimental design and probe mapping efforts behind the MAQC project. We show intraplatform consistency across test sites as well as a high level of interplatform concordance in terms of genes identified as differentially expressed. This study provides a resource that represents an important first step toward establishing a framework for the use of microarrays in clinical and regulatory settings.

1. Contrast the current strengths and limitations of the three main slide-based techniques (IHC, FISH, and CISH) currently in clinical use for testing breast cancer tissues for HER-2 status.2. Compare the efficacy of trastuzumab-and lapatinib-based regimens in the adjuvant and metastatic settings as reported in published clinical trials and regulatory approval databases.3. Contrast the list of biomarkers that have been associated with clinical resistance to trastuzumab and lapatinib and describe their current level of validation.This article is available for continuing medical education credit at CME.TheOncologist.com. CME CME ABSTRACTThe human epidermal growth factor receptor (HER-2) oncogene encodes a transmembrane tyrosine kinase receptor that has evolved as a major classifier of invasive breast cancer and target of therapy for the disease. The validation of the general prognostic significance of HER-2 gene amplification and protein overexpression in the absence of anti-HER-2 targeted therapy is discussed in a study of 107 published studies involving 39,730 patients, which produced an overall HER-2-positive rate of 22.2% and a mean relative risk for overall survival (OS) of 2.74. The issue of HER-2 status in primary versus metastatic breast cancer is considered along with a section on the features of metastatic HER-2-positive disease. The major marketed slide-based HER-2 testing approaches, immunohistochemistry, fluorescence in situ hybridization, and chromogenic in situ

CONTEXT Accurate prediction of who will (or won’t) have high probability of survival benefit from standard treatments is fundamental for individualized cancer treatment strategies. OBJECTIVE To develop a predictor of response and survival from chemotherapy for newly diagnosed invasive breast cancer. DESIGN Development of different predictive signatures for resistance and response to neoadjuvant chemotherapy (stratified according to estrogen receptor (ER) status) from gene expression microarrays of newly diagnosed breast cancer (310 patients). Then prediction of breast cancer treatment-sensitivity using the combination of signatures for: 1) sensitivity to endocrine therapy, 2) chemo-resistance, and 3) chemo-sensitivity. Independent validation (198 patients) and comparison with other reported genomic predictors of chemotherapy response. SETTING Prospective multicenter study to develop and test genomic predictors for neoadjuvant chemotherapy. PATIENTS Newly diagnosed HER2-negative breast cancer treated with chemotherapy containing sequential taxane and anthracycline-based regimens then endocrine therapy (if hormone receptor-positive). MAIN OUTCOME MEASURES Distant relapse-free survival (DRFS) if predicted treatment-sensitive and absolute risk reduction (ARR, difference in DRFS of the two predicted groups) at median follow-up (3 years), and their 95% confidence intervals (CI). RESULTS Patients in the independent validation cohort (99% clinical Stage II–III) who were predicted to be treatment-sensitive (28% of total) had DRFS of 92% (CI 85–100) and survival benefit compared to others (absolute risk reduction (ARR) 18%; CI 6–28). Predictions were accurate if breast cancer was ER-positive (30% predicted sensitive, DRFS 97%, CI 91–100; ARR 11%, CI 0.1–21) or ER-negative (26% predicted sensitive, DRFS 83%, CI 68–100; ARR 26%, CI 4–28), and were significant in multivariate analysis after adjusting for relevant clinical-pathologic characteristics. Other genomic predictors showed paradoxically worse survival if predicted to be responsive to chemotherapy. CONCLUSION A genomic predictor combining ER status, predicted chemo-resistance, predicted chemo-sensitivity, and predicted endocrine sensitivity accurately identified patients with survival benefit following taxane-anthracycline chemotherapy.