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Purpose: We previously demonstrated the clinical significance of circulating tumor DNA (ctDNA) in patients with HER2-negative breast cancer receiving neoadjuvant chemotherapy (NAC). Here, we compared its predictive and prognostic value with cell-free DNA (cfDNA) concentration measured in the same samples from the same patients., Experimental Design: 145 patients with hormone receptor (HR)-positive/HER2-negative and 138 triple-negative breast cancer (TNBC) with ctDNA data from a previous study were included in the analysis. Associations of serial cfDNA concentration with residual cancer burden (RCB) and distant recurrence-free survival (DRFS) were examined., Results: In TNBC, we observed a modest negative correlation between cfDNA concentration 3 weeks after treatment initiation and RCB, but none of the other timepoints showed significant correlation. In contrast, ctDNA was significantly positively correlated with RCB at all timepoints (all R > 0.3 and P < 0.05). In the HR-positive/HER2-negative group, cfDNA concentration did not associate with response to NAC, but survival analysis showed that high cfDNA shedders at pretreatment had a significantly worse DRFS than low shedders (hazard ratio, 2.12; P = 0.037). In TNBC, the difference in survival between high versus low cfDNA shedders at all timepoints was not statistically significant. In contrast, as previously reported, ctDNA at all timepoints was significantly correlated with DRFS in both subtypes., Conclusions: In TNBC, cfDNA concentrations during therapy were not strongly correlated with response or prognosis. In the HR-positive/HER2-negative group, pretreatment cfDNA concentration was prognostic for DRFS. Overall, the predictive and prognostic value of cfDNA concentration was more limited than that of ctDNA., (©2024 American Association for Cancer Research.)

Purpose: The neutralizing peptibody trebananib prevents angiopoietin-1 and angiopoietin-2 from binding with Tie2 receptors, inhibiting angiogenesis and proliferation. Trebananib was combined with paclitaxel±trastuzumab in the I-SPY2 breast cancer trial., Patients and Methods: I-SPY2, a phase II neoadjuvant trial, adaptively randomizes patients with high-risk, early-stage breast cancer to one of several experimental therapies or control based on receptor subtypes as defined by hormone receptor (HR) and HER2 status and MammaPrint risk (MP1, MP2). The primary endpoint is pathologic complete response (pCR). A therapy "graduates" if/when it achieves 85% Bayesian probability of success in a phase III trial within a given subtype. Patients received weekly paclitaxel (plus trastuzumab if HER2-positive) without (control) or with weekly intravenous trebananib, followed by doxorubicin/cyclophosphamide and surgery. Pathway-specific biomarkers were assessed for response prediction., Results: There were 134 participants randomized to trebananib and 133 to control. Although trebananib did not graduate in any signature [phase III probabilities: Hazard ratio (HR)-negative (78%), HR-negative/HER2-positive (74%), HR-negative/HER2-negative (77%), and MP2 (79%)], it demonstrated high probability of superior pCR rates over control (92%-99%) among these subtypes. Trebananib improved 3-year event-free survival (HR 0.67), with no significant increase in adverse events. Activation levels of the Tie2 receptor and downstream signaling partners predicted trebananib response in HER2-positive disease; high expression of a CD8 T-cell gene signature predicted response in HR-negative/HER2-negative disease., Conclusions: The angiopoietin (Ang)/Tie2 axis inhibitor trebananib combined with standard neoadjuvant therapy increased estimated pCR rates across HR-negative and MP2 subtypes, with probabilities of superiority >90%. Further study of Ang/Tie2 receptor axis inhibitors in validated, biomarker-predicted sensitive subtypes is warranted., (©2023 American Association for Cancer Research.)

Purpose: To evaluate prediction of response and event-free survival (EFS) following neoadjuvant endocrine therapy by SET2,3 index of nonproliferation gene expression related to estrogen and progesterone receptors adjusted for baseline prognosis., Experimental Design: A correlative study was conducted of SET2,3 measured from gene expression profiles of diagnostic tumor (Agilent microarrays) in 379 women with cStage II-III breast cancer from the American College of Surgeons Oncology Group Z1031 neoadjuvant aromatase inhibitor trial SET2,3 was dichotomized using the previously published cutoff. Fisher exact test was used to assess the association between SET2,3 and low proliferation at week 2-4 [Ki67 ≤ 10% or complete cell-cycle arrest (CCCA; Ki67 ≤ 2.7%)] and PEPI-0 rate in cohort B, and the association between SET2,3 and ypStage 0/I in all patients. Cox models were used to assess EFS with respect to SET2,3 excluding cohort B patients who switched to chemotherapy., Results: Patients with high SET2,3 had higher rate of pharmacodynamic response than patients with low SET2,3 (Ki67 ≤ 10% in 88.2% vs. 56.9%, P < 0.0001; CCCA in 50.0% vs. 26.2%, P = 0.0054), but rate of ypStage 0/I (24.0% vs. 20.4%, P = 0.4580) or PEPI = 0 (28.4% vs. 20.6%, P = 0.3419) was not different. Patients with high SET2,3 had longer EFS than patients with low SET2,3 (HR, 0.52, 95% confidence interval: 0.34-0.80; P = 0.0026)., Conclusions: This exploratory analysis of Z1031 data demonstrated a higher rate of pharmacodynamic suppression of proliferation and longer EFS in high SET2,3 disease relative to low SET2,3 disease. The ypStage 0/I rate and PEPI = 0 rate were similar with respect to SET2,3., (©2022 The Authors; Published by the American Association for Cancer Research.)

Predictive biomarkers for immune therapy must address a complex interface between the immune system and triple-negative breast cancer and still be technically reliable for diagnostic use. Two recent articles describe the assessment of spatial heterogeneity using digital methods that promise to improve the quantification of immune infiltrate or molecular targets. See related articles by Bai et al., p. 5557 and Carter et al., p. 5628 ., (©2021 American Association for Cancer Research.)

Purpose: Low molecular weight cyclin E (LMW-E) detected by Western blot analysis predicts for reduced breast cancer survival; however, it is impractical for clinical use. LMW-E lacks a nuclear localization signal that leads to accumulation in the cytoplasm that can be detected by IHC. We tested the hypothesis that cytoplasmic staining of cyclin E can be used as a predictor of poor outcome in different subtypes of breast cancer using patient cohorts with distinct clinical and pathologic features. Experimental Design: We evaluated the subcellular localization of cyclin E in breast cancer specimens from 2,494 patients from 4 different cohorts: 303 from a prospective study and 2,191 from retrospective cohorts [NCI, MD Anderson Cancer Center (MDA), and the United Kingdom (UK)]. Median follow-up times were 8.0, 10.1, 13.5, and 5.7 years, respectively. Results: Subcellular localization of cyclin E on IHC was associated with full-length (nuclear) and low molecular weight isoforms (cytoplasmic) of cyclin E on Western blot analysis. In multivariable analysis, cytoplasmic cyclin E staining was associated with the greatest risk of recurrence compared with other prognostic factors across all subtypes in three (NCI, MDA, and UK) of the cohorts. In the MDA cohort, cytoplasmic cyclin E staining outperformed Ki67 and all other variables as prognostic factors. Conclusions: Cytoplasmic cyclin E identifies patients with the highest likelihood of recurrence consistently across different patient cohorts and subtypes. These patients may benefit from alternative therapies targeting the oncogenic isoforms of cyclin E. Clin Cancer Res; 23(12); 2991-3002. ©2016 AACR ., (©2016 American Association for Cancer Research.)

Purpose: Pathologic complete response (pCR) to neoadjuvant chemotherapy reflects the cytotoxic efficacy of a drug, but patient survival is influenced by many other factors. The purpose of this study was to assess the relationship between increased pCR rate and trial-level survival benefit in triple-negative breast cancer (TNBC)., Experimental Design: We used bootstrap resampling from a neoadjuvant trial to simulate trials with different pCR rates. We used estimates from Adjuvant!Online to simulate trial populations with different baseline prognosis and estimated survival improvements associated with changes in pCR rate., Results: Assuming that survival is similar for patients with pCR regardless of treatment arm, a linear relationship exists between increasing pCR rate and increasing recurrence-free survival (RFS). The slope is equal to the difference in survival between those with pCR and residual disease, which in turn is influenced by (i) the baseline prognosis of the trial population, (ii) interactions between prognostic variables and pCR, and (iii) the efficacy of the postneoadjuvant therapies. For example, if the pCR rates are 30% and 60% (OR = 3.5) and the 10-year RFS of the control arm is 0.74, the trial would require 3,550 patients per arm, whereas if the RFS is 0.54, the trial would require only 425 patients per arm to detect significant survival benefit., Conclusions: We provide a framework for understanding the relationship between pCR and overall survival benefit that can help inform the design of neoadjuvant trials aiming to demonstrate improved survival from a regimen that results in higher pCR rate., (©2015 American Association for Cancer Research.)

The article by Rouzier and colleagues, published in the August 15, 2005, issue of Clinical Cancer Research, demonstrated that different molecular subtypes of breast cancer have different degrees of sensitivity to chemotherapy, but the extent of response to neoadjuvant therapy has a different meaning by subtype. Several molecular subtype-specific clinical trials are under way to maximize pathologic complete response rates in triple-negative breast cancer and HER2-positive cancers, and to provide adjuvant treatment options for patients with residual invasive disease. See related article by Rouzier et al., Clin Cancer Res 2005;11(16) Aug 15, 2005;5678-85., (©2015 American Association for Cancer Research.)

Purpose: Dasatinib has limited single-agent activity in unselected patients with metastatic breast cancer. Several gene signatures predictive of dasatinib response in vitro have been reported. The purpose of this three-arm, phase II study was to prospectively assess the utility of three previously published gene signatures to select patients with clinical benefit from dasatinib., Experimental Design: Patients with metastatic breast cancer underwent biopsy for gene expression profiling in an academic CLIA laboratory; those who were positive for any one of three predictive gene signatures (dasatinib sensitivity signature, SRC pathway activity signature, and dasatinib target index) received dasatinib 100 mg orally daily. The three marker-defined cohorts were analyzed separately, using early stopping rules for futility., Results: Ninety-seven patients were enrolled, 93 underwent biopsy, and 80% of the biopsies were sufficient for molecular testing. Thirty patients were positive for at least one signature and received treatment. Only 1 patient experienced clinical benefit and had stable disease over 300 days. All three arms were closed early for futility. There was one serious biopsy-related adverse event (hematoma and pain following a liver biopsy). There were no unexpected toxicities from dasatinib., Conclusion: None of the three predictive gene signatures, although supported by preclinical evidence, defined tumors clinically sensitive to dasatinib as a single agent., (©2014 American Association for Cancer Research.)

Purpose: The clinical relevancy of the 7-subtype classification of triple-negative breast cancer (TNBC) reported by Lehmann and colleagues is unknown. We investigated the clinical relevancy of TNBC heterogeneity by determining pathologic complete response (pCR) rates after neoadjuvant chemotherapy, based on TNBC subtypes., Experimental Design: We revalidated the Lehmann and colleagues experiments using Affymetrix CEL files from public datasets. We applied these methods to 146 patients with TNBC with gene expression microarrays obtained from June 2000 to March 2010 at our institution. Of those, 130 had received standard neoadjuvant chemotherapy and had evaluable pathologic response data. We classified the TNBC samples by subtype and then correlated subtype and pCR status using Fisher exact test and a logistic regression model. We also assessed survival and compared the subtypes with PAM50 intrinsic subtypes and residual cancer burden (RCB) index., Results: TNBC subtype and pCR status were significantly associated (P = 0.04379). The basal-like 1 (BL1) subtype had the highest pCR rate (52%); basal-like 2 (BL2) and luminal androgen receptor had the lowest (0% and 10%, respectively). TNBC subtype was an independent predictor of pCR status (P = 0.022) by a likelihood ratio test. The subtypes better predicted pCR status than did the PAM50 intrinsic subtypes (basal-like vs. non basal-like)., Conclusions: Classifying TNBC by 7 subtypes predicts high versus low pCR rate. We confirm the clinical relevancy of the 7 subtypes of TNBC. We need to prospectively validate whether the pCR rate differences translate into long-term outcome differences. The 7-subtype classification may spur innovative personalized medicine strategies for patients with TNBC., (©2013 AACR.)

Purpose: Patients with triple-negative breast cancer (TNBC) and residual disease after neoadjuvant chemotherapy generally have worse outcome; however, some patients with residual tumor after neoadjuvant chemotherapy do not relapse. We hypothesize that there are subgroups of patients with chemoresistant TNBC with different prognosis., Experimental Design: Forty-nine chemoresistant cases from 111 patients with TNBC treated with neoadjuvant chemotherapy (M.D. Anderson Cancer Center, Houston, TX) constituted the discovery cohort, and 25 chemoresistant samples from 47 neoadjuvant chemotherapy-treated TNBC (The Methodist Hospital, Houston, TX) were chosen for validation. Extended validation was carried out in 269 operable TNBC predicted to be chemoresistant by expression pattern from published datasets., Results: We established a seven-gene prognostic signature using dChip and gene set enrichment analyses. In the independent validation cohort, the classifier predicted correctly with positive predictive value of 75.0% and negative predictive value (i.e., relapse-free survival; RFS) of 76.9% at 3 years. Those predicted to relapse had a HR of 4.67 [95% confidence interval (CI): 1.27-17.15] for relapse in 3 years. In extended validation, patients predicted not to relapse exhibited 3-year RFS of 78.9%, whereas the 3-year RFS was 48.5% for patients predicted to relapse, with HR of 2.61 (95% CI: 1.52-4.49). The TNBC subgroup that predicted to have relatively favorable prognosis was characterized by high expression of "luminal-like" genes [androgen-receptor (AR) and GATA3], whereas the subgroup with worse prognosis was characterized by expression of cancer stem-cell markers., Conclusion: We developed a clinically relevant signature for patients with chemoresistant TNBC. For these women, new therapeutic strategies like targeting AR activation or cancer stem cells may need to be developed., (©2013 AACR)

Purpose: To examine gene expression differences between pre- and post-neoadjuvant systemic therapy (NST) specimens of breast cancers and identify biologic changers that may lead to new therapeutic insights., Methods: Gene expression data from prechemotherapy fine needle aspiration specimens were compared with resected residual cancers in 21 patients after 4 to 6 months of NST. We removed stroma-associated genes to minimize confounding effects. PAM50 was used to assign molecular class. Paired t test and gene set analysis were used to identify differentially expressed genes and pathways., Results: The ER and HER2 status based on mRNA expression remained stable in all but two cases, and there were no changes in proliferation metrics (Ki67 and proliferating cell nuclear antigen expression). Molecular class changed in 8 cases (33.3%), usually to normal-like class, which was associated with low residual cancer cell cellularity. The expression of 200 to 600 probe sets changed between baseline and post-NST samples. In basal-like cancers, pathways driven by increased expression of phosphoinositide 3-kinase, small G proteins, and calmodulin-dependent protein kinase II and energy metabolism were enriched, whereas immune cell-derived and the sonic hedgehog pathways were depleted in residual cancer. In non-basal-like breast cancers, notch signaling and energy metabolism (e.g., fatty acid synthesis) were enriched and sonic hedgehog signaling and immune-related pathways were depleted in residual cancer. There was no increase in epithelial-mesenchymal transition or cancer stem cell signatures., Conclusions: Our data indicate that energy metabolism related processes are upregulated and immune-related signals are depleted in residual cancers. Targeting these biologic processes may represent promising adjuvant treatment strategies for patients with residual cancer.

Purpose: Estrogen receptor-positive (ER+) and -negative (ER) breast cancers are molecularly distinct diseases. We hypothesized that p53 mutations may lead to different transcriptional changes and carry different prognostic value in these two different types of cancers., Experimental Design: We developed a 39-gene p53 signature derived from 213 ER+ and a separate 30-gene signature from 38 ER- cancers with known mutation status and tested their prognostic and chemotherapy response predictive values in ER+ and ER- cancers, respectively., Results: External validation to predict p53 status (n = 103) showed sensitivity and specificity of 89% and 54% for the 39-gene signature, and 82% and 61% for the 30-gene signature. The 39-gene signature was predictive of worse distant metastasis free survival in ER+ cancers in two separate prognostic data sets (n = 255, HR: 2.3, P = 0.005 and n = 198, HR: 2.17, P = 0.09). It also predicted for poor prognosis even with adjuvant tamoxifen therapy (n = 277, HR = 2.43, P < 0.0001) but it was not prognostic in ER- cancers. It was also associated with higher chemotherapy sensitivity in ER+ but not in ER- cancers. The prognostic and predictive values remained significant in multivariate analysis. The 30-gene, ER-, p53 signature showed no prognostic or predictive values in ER+ cancers but it was associated with better prognosis in ER- cancers. It also had no chemotherapy response predictive value in ER- or ER+ cancers., Conclusions: P53 dysfunction is prognostically most relevant in ER+ cancers and supports the hypothesis that different predictive or prognostic markers will be needed for different molecular subsets of breast cancer., (©2011 AACR.)

Purpose: We examined in a prospective, randomized, international clinical trial the performance of a previously defined 30-gene predictor (DLDA-30) of pathologic complete response (pCR) to preoperative weekly paclitaxel and fluorouracil, doxorubicin, and cyclophosphamide (T/FAC) chemotherapy, and assessed if DLDA-30 also predicts increased sensitivity to FAC-only chemotherapy. We compared the pCR rates after T/FAC versus FACx6 preoperative chemotherapy. We also did an exploratory analysis to identify novel candidate genes that differentially predict response in the two treatment arms., Experimental Design: Two hundred and seventy-three patients were randomly assigned to receive either weekly paclitaxel × 12 followed by FAC × 4 (T/FAC, n = 138), or FAC × 6 (n = 135) neoadjuvant chemotherapy. All patients underwent a pretreatment fine-needle aspiration biopsy of the tumor for gene expression profiling and treatment response prediction., Results: The pCR rates were 19% and 9% in the T/FAC and FAC arms, respectively (P < 0.05). In the T/FAC arm, the positive predictive value (PPV) of the genomic predictor was 38% [95% confidence interval (95% CI), 21-56%], the negative predictive value was 88% (95% CI, 77-95%), and the area under the receiver operating characteristic curve (AUC) was 0.711. In the FAC arm, the PPV was 9% (95% CI, 1-29%) and the AUC was 0.584. This suggests that the genomic predictor may have regimen specificity. Its performance was similar to a clinical variable-based predictor nomogram., Conclusions: Gene expression profiling for prospective response prediction was feasible in this international trial. The 30-gene predictor can identify patients with greater than average sensitivity to T/FAC chemotherapy. However, it captured molecular equivalents of clinical phenotype. Next-generation predictive markers will need to be developed separately for different molecular subsets of breast cancers., (©2010 AACR.)

Purpose: Several different multivariate prediction models using routine clinical variables or multigene signatures have been proposed to predict pathologic complete response to combination chemotherapy in breast cancer. Our goal was to compare the performance of four conceptually different predictors in an independent cohort of patients., Experimental Design: Gene expression profiling was done on fine-needle aspirations of 100 stage I to III breast cancers before preoperative paclitaxel, 5-fluorouracil, doxorubicin, and cyclophosphamide combination chemotherapy. Pathologic response was correlated with prediction results from a clinical nomogram, a human cancer-derived genomic predictor (DLDA30), a cell line-based genomic predictor [in vitro coexpression extrapolation (COXEN)], and an optimized cell line-derived (in vivo COXEN) predictor. None of the 100 test cases were used in the development of these predictors., Results: The in vitro COXEN using a combination of four individual drug sensitivity predictions derived from cell lines was not predictive [area under the receiver operator characteristic curve (AUC), 0.5; 95% confidence interval, (95% CI), 0.41-0.59]. The clinical nomogram (AUC, 0.73; 95% CI, 0.65-0.80) and the DLDA30 (AUC, 0.73; 95% CI, 0.66-0.80) genomic predictor had similar performances. The in vivo COXEN that used informative genes from cell lines but was trained on a separate human data set also showed significant predictive value (AUC, 0.67; 95% CI, 0.60-0.74). These three different prediction scores correlated with each other and were significant in univariate but not in multivariate analysis., Conclusions: Three conceptually different predictors performed similarly in this validation study and tended to identify the same patients as responders. A genomic predictor that relied solely on a composite of individual drug sensitivity predictions from cell lines did not show any predictive value.

Purpose: We used high-resolution oligonucleotide comparative genomic hybridization (CGH) arrays and matching gene expression array data to identify dysregulated genes and to classify breast cancers according to gene copy number anomalies., Experimental Design: DNA was extracted from 106 pretreatment fine needle aspirations of stage II-III breast cancers that received preoperative chemotherapy. CGH was done using Agilent Human 4 x 44K arrays. Gene expression data generated with Affymetrix U133A gene chips was also available on 103 patients. All P values were adjusted for multiple comparisons., Results: The average number of copy number abnormalities in individual tumors was 76 (range 1-318). Eleven and 37 distinct minimal common regions were gained or lost in >20% of samples, respectively. Several potential therapeutic targets were identified, including FGFR1 that showed high-level amplification in 10% of cases. Close correlation between DNA copy number and mRNA expression levels was detected. Nonnegative matrix factorization (NMF) clustering of DNA copy number aberrations revealed three distinct molecular classes in this data set. NMF class I was characterized by a high rate of triple-negative cancers (64%) and gains of 6p21. VEGFA, E2F3, and NOTCH4 were also gained in 29% to 34% of triple-negative tumors. A gain of ERBB2 gene was observed in 52% of NMF class II and class III was characterized by a high rate of estrogen receptor-positive tumors (73%) and a low rate of pathologic complete response to preoperative chemotherapy (3%)., Conclusion: The present study identified dysregulated genes that could classify breast cancer and may represent novel therapeutic targets for molecular subsets of cancers.

Purpose: Preclinical data showed enhancement of breast cancer cell death when G3139 was combined with anthracyclines and taxanes. We evaluated the efficacy and safety of a Bcl-2 antisense oligonucleotide, G3139, in combination with doxorubicin (A) and docetaxel (T) in patients with locally advanced breast cancer (LABC)., Experimental Design: Following a brief phase I to determine the phase II dose, patients with locally advanced breast cancer received G3139 administered by continuous i.v. infusion for 5 to 7 days with bolus A (50 mg/m2) and T (75 mg/m2) administered on either day 3 or 6 of therapy with G3139. Cycles were repeated every 21 days x 6 in the neoadjuvant setting. Serial plasma samples were obtained for pharmacokinetic analysis. Tissue samples were obtained before and after therapy for pharmacodynamic analysis of Bcl-2 expression., Results: Thirty patients (median age, 49 years; range, 24-71 years) received 160 cycles. During the phase I portion of the trial, the dose of G3139 was escalated from 3 to 7 mg/kg/d (i.v. for 5 days) in combination with AT. During the phase II portion of the trial, several doses and schedules of G3139 were evaluated. There were no pathologic complete responses. Pharmacodynamic studies showed limited Bcl-2 down-regulation in the primary tumors., Conclusions: G3139 in combination with doxorubicin and docetaxel is well tolerated. No pathologic complete response was seen and pharmacodynamic studies showed very little down-regulation of Bcl-2 in primary tumors, perhaps related to issues with insufficient drug delivery to the intact tumor.

Purpose: We examined whether the response predicted by a 30-gene pharmacogenomic test correlated with the residual cancer burden (RCB) after preoperative chemotherapy with paclitaxel, 5-fluorouracil, doxorubicin, and cyclophosphamide (T/FAC)., Experimental Design: Gene expression profiling was done at diagnosis in 74 patients with stages I to III breast cancer and was used to calculate a pharmacogenomic score and predict response to chemotherapy [pathologic complete response (pCR) or residual disease (RD)]. All patients received 6 months of preoperative T/FAC. Following pathologic review, a RCB score was calculated based on residual tumor and lymph node features. Four RCB classes were assigned; RCB-0 (pCR), RCB-I (near-PCR), RCB-II (moderate RD), and RCB-III (extensive RD). The correlations between the pharmacogenomic score, predicted pathologic response, RCB score, and RCB class were examined., Results: Thirty-three patients were predicted to have pCR, and 40 were predicted to have RD. Observed responses were RCB-0: n=20 (27%); RCB-I: n=5 (7%); RCB-II: n=36 (49%); and RCB-III: n=13 (16%) patients. Pharmacogenomic and RCB scores were correlated (Pearson's R=-0.501, P<0.0001). There was no difference between the mean genomic predictor scores for RCB-0/I groups (P=0.94), but these were different from the mean scores of the RCB-II/III groups (P<0.001). Among the 25 patients with RCB-0/I response, 19 (76%) were predicted to achieve pCR. The pharmacogenomic test correctly predicted RD in 92% of the patients with RCB-III, which corresponds to chemotherapy-resistant disease., Conclusions: The 30-gene pharmacogenomic test showed good correlation with the extent of residual invasive cancer burden measured as both continuous and categorical variables.

Despite the rapid expansion of novel diagnostics designed to personalize breast cancer care, there remain several significant unmet needs for improving the accuracy and reliability of tests that are already in common daily clinical practice. For example, although immunohistochemistry has been the predominant method for measuring estrogen receptor and progesterone receptor status for over 15 years, this assay remains unstandardized and there is a widespread concern that inaccuracy in immunohistochemistry technique and interpretation is leading to an unacceptably high error rate in determining the true hormone receptor status. Similarly, there is considerable concern that both false-negative and false-positive result rates for testing for HER2 status are unacceptably high in current clinical practice. This commentary considers a variety of factors, including preanalytic conditions and slide-scoring procedures, and other variables that may be contributing to current testing error rates and why there is a great need for the standardization of these biomarker assay procedures to further enable the highest possible quality of care for newly diagnosed breast cancer patients.

Purpose: The clinical outcome for patients with breast cancer is influenced by the metastatic competence of the cancer and its sensitivity to endocrine therapy and chemotherapy. A molecular marker may be prognostic of outcome or predictive of response to therapy, or a combination of both., Experimental Design: We examined separately the prognostic and predictive values of tau mRNA expression in estrogen receptor (ER)-positive primary breast cancers in three patient cohorts. We used gene expression data from 209 untreated patients to assess the pure prognostic value of tau, data from 267 patients treated with adjuvant tamoxifen to assess predictive value for endocrine therapy, and data from 82 patients treated with preoperative paclitaxel followed by 5-fluorouracil, doxorubicin, and cyclophosphamide (paclitaxel/FAC) to assess predictive value for chemotherapy response. Wilcoxon rank sum test was used to compare tau expression between different outcome groups., Results: Higher tau mRNA expression showed borderline nonsignificant association with better prognosis in the absence of systemic adjuvant therapy. Higher tau mRNA expression was significantly associated with no recurrence (at 5 and 10 years, P = 0.005 and P = 0.05, respectively) in patients treated with tamoxifen, indicating a predictive value for endocrine therapy. Tau expression was significantly lower in patients who achieved pathologic complete response to paclitaxel/FAC chemotherapy (P < 0.001)., Conclusion: This study suggests that high tau mRNA expression in ER-positive breast cancer indicates an endocrine-sensitive but chemotherapy-resistant disease. In contrast, low tau expression identifies a subset of ER-positive cancers that have poor prognosis with tamoxifen alone and may benefit from taxane-containing chemotherapy.

Purpose: The goals of this analysis were to (a) determine concordance of gene expression results from replicate experiments, (b) examine prediction agreement of multigene predictors on replicate data, and (c) assess the robustness of prediction results in the face of noise., Patients and Methods: Affymetrix U133A gene chips were used for gene expression profiling of 97 fine-needle aspiration biopsies from breast cancer. Thirty-five cases were profiled in replicates: 17 within the same laboratory, 11 in two different laboratories, and 15 to assess manual and robotic labeling. We used data from 62 cases to develop 111 distinct pharmacogenomic predictors of response to therapy. These were tested on cases profiled in duplicates to determine prediction agreement and accuracy. To evaluate the robustness of the pharmacogenomic predictors, we also introduced random noise into the informative genes in one half of the replicates., Results: The average concordance correlation coefficient was 0.978 (range, 0.96-0.99) for intralaboratory replicates, 0.962 (range, 0.94-0.98) for between-laboratory replicates, and 0.971 (range, 0.93-0.99) for manual versus robotic labeling. The mean % prediction agreement on replicate data was 97% (95% CI, 0.96-0.98; SD, 0.006), 92% (95% CI, 0.90-0.93; SD, 0.009), and 94% (95% CI, 0.92-0.95; SD, 0.008) for support vector machines, diagonal linear discriminant analysis, and k-nearest neighbor prediction methods, respectively. Mean accuracy in the test set was 77% (95% CI, 0.74-0.79; SD, 0.014), 66% (95% CI, 0.63-0.73; SD, 0.015), and 64% (95% CI, 0.60-0.67; SD, 0.016), respectively., Conclusion: Gene expression results obtained with Affymetrix U133A chips are highly reproducible within and across two high-volume laboratories. Pharmacogenomic predictions yielded >90% agreement in replicate data.

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 61 genes 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 normal-like cancers.

Purpose: The purpose of this study was to determine whether comprehensive transcriptional profiles (TPs) can be obtained from single-passage fine-needle aspirations (FNAs) of breast cancer and to explore whether profiles capture routine clinicopathological parameters., Experimental Design: Expression profiles were available on 38 patients with stage I-III breast cancer who underwent FNA at the time of diagnosis. [(33)P]dCTP-labeled cDNA probes were generated and hybridized to cDNA membrane microarrays that contained 30,000 human sequence clones, including 10,890 expressed sequence tags., Results: The median total RNA yield from the biopsies was 2 micro g (range, 1-25 micro g). The cellular composition of each biopsy was examined and, on average, 79% of the cells were cancer cells. TP was successfully performed on all 38 of the biopsies. Unsupervised complete-linkage hierarchical clustering with all of the biopsies revealed an association between estrogen receptor (ER) status and gene expression profiles. There was a strong correlation between ER status determined by TP and measured by routine immunohistochemistry (P = 0.001). A similar strong correlation was seen with HER-2 status determined by fluorescent in situ hybridization (P = 0.0002). Using the first 18 cases as the discovery set, we established a cutoff of 2.0 and 18.0 for ER and HER-2 mRNA levels, respectively, to distinguish clinically-negative from -positive cases. We also identified 105 genes (excluding the ER gene) the expression of which correlated highly with clinical ER status. Twenty tumors were used for prospective validation. HER-2 status was correctly identified in all 20 of the cases, based on HER-2 mRNA content detected by TP. ER status was correctly identified in 19 of 20 cases. When the marker set of 105 genes was used to prospectively predict ER status, TP-based classification correctly identified 9 of 10 of the ER-positive and 7 of 10 of the ER-negative tumors. We also explored supervised cluster analysis using various functional categories of genes, and we observed a clear separation between ER-negative and ER-positive tumors when genes involved in signal transduction were used for clustering., Conclusions: These results demonstrate that comprehensive TP can be performed on FNA biopsies. TPs reliably measure conventional single-gene prognostic markers such as ER and HER-2. A complex pattern of genes (not including ER) can also be used to predict clinical ER status. These results demonstrate that needle biopsy-based diagnostic microarray tests may be developed that could capture conventional prognostic information but may also contain additional clinical information that cannot currently be measured with other methods.