Keith Anderson

Breast Cancer Molecular Subtypes Respond Differently to Preoperative Chemotherapy

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.

Pharmacogenomic Predictor of Sensitivity to Preoperative Chemotherapy With Paclitaxel and Fluorouracil, Doxorubicin, and Cyclophosphamide in Breast Cancer

PURPOSE We developed a multigene predictor of pathologic complete response (pCR) to preoperative weekly paclitaxel and fluorouracil-doxorubicin-cyclophosphamide (T/FAC) chemotherapy and assessed its predictive accuracy on independent cases. PATIENTS AND METHODS One hundred thirty-three patients with stage I-III breast cancer were included. Pretreatment gene expression profiling was performed with oligonecleotide microarrays on fine-needle aspiration specimens. We developed predictors of pCR from 82 cases and assessed accuracy on 51 independent cases. RESULTS Overall pCR rate was 26% in both cohorts. In the training set, 56 probes were identified as differentially expressed between pCR versus residual disease, at a false discovery rate of 1%. We examined the performance of 780 distinct classifiers (set of genes + prediction algorithm) in full cross-validation. Many predictors performed equally well. A nominally best 30-probe set Diagonal Linear Discriminant Analysis classifier was selected for independent validation. It showed significantly higher sensitivity (92% v 61%) than a clinical predictor including age, grade, and estrogen receptor status. The negative predictive value (96% v 86%) and area under the curve (0.877 v 0.811) were nominally better but not statistically significant. The combination of genomic and clinical information yielded a predictor not significantly different from the genomic predictor alone. In 31 samples, RNA was hybridized in replicate with resulting predictions that were 97% concordant. CONCLUSION A 30-probe set pharmacogenomic predictor predicted pCR to T/FAC chemotherapy with high sensitivity and negative predictive value. This test correctly identified all but one of the patients who achieved pCR (12 of 13 patients) and all but one of those who were predicted to have residual disease had residual cancer (27 of 28 patients).

Determination of oestrogen-receptor status and ERBB2 status of breast carcinoma: a gene-expression profiling study.

BACKGROUND Gene expression microarrays are being used to develop new prognostic and predictive tests for breast cancer, and might be used at the same time to confirm oestrogen-receptor status and ERBB2 status. Our goal was to establish a new method to assign oestrogen receptor and ERBB2-receptor status to breast carcinoma based on mRNA expression measured using Affymetrix U133A gene-expression profiling. METHODS We used gene expression data of 495 breast cancer samples to assess the correlation between oestrogen receptor (ESR1) and ERBB2 mRNA and clinical status of these genes (as established by immunohistochemical [IHC] or fluorescence in-situ hybridisation [FISH], or both). Data from 195 fine-needle aspiration (FNA) samples were used to define mRNA cutoff values that assign receptor status. We assessed the accuracy of these cutoffs in two independent datasets: 123 FNA samples and 177 tissue samples (ie, resected or core-needle biopsied tissues). Profiling was done at two institutions by use of the same platform (Affymetrix U133A GeneChip). All data were uniformly normalised with dCHIP software. FINDINGS ESR1 and ERBB2 mRNA levels correlated closely with routine measurements for receptor status in all three datasets. Spearmans correlation coefficients ranged from 0.62 to 0.77. An ESR1 mRNA cutoff value of 500 identified oestrogen-receptor-positive status with an overall accuracy of 90% (training set), 88% (first validation set), and 96% (second validation set). An ERBB2 mRNA threshold of 1150 identified ERBB2-positive status with the overall accuracy of 93% (training set), 89% (first validation set), and 90% (second validation set). Reproducibility of mRNA measurements in 34 replicate experiments was high (correlation coefficient 0.975 for ESR1, 0.984 for ERBB2). INTERPRETATION Amounts of ESR1 and ERBB2 mRNA as measured by the Affymetrix GeneChip reliably and reproducibly establish oestrogen-receptor status and ERBB2 status, respectively.

Microtubule-associated protein-tau is a bifunctional predictor of endocrine sensitivity and chemotherapy resistance in estrogen receptor-positive breast cancer

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.

Pharmacogenomic Predictor Discovery in Phase II Clinical Trials for Breast Cancer

Purpose: We examined if supervised analysis of gene expression data from phase II studies could identify HER-2 overexpression as a predictor of response to trastuzumab. Experimental Design: Gene expression data from 132 newly diagnosed breast cancers were used to simulate 50,000 single-agent phase II trastuzumab studies. True HER-2 amplification was assessed by fluorescence in situ hybridization. Results: Only 3.67% of the simulated studies yielded HER-2 as the top predictor, >96% of the individual “studies” picked a different gene as the most predictive of trastuzumab response. HER-2 was included in the top 10 gene list 9.73% of the time. When HER-2 was a priori defined as a potential predictor, 99.6% of the simulated studies confirmed overexpression among responders. Candidate marker testing may be more efficient than de novo predictor discovery in phase II trials. We describe a tandem, two-step phase II trial design for rapid marker assessment that combines two optimal two-stage phase II trials into a single study. In the first stage, unselected patients are treated, and if insufficient responses are seen, the trial remains open for marker-positive patients only and a second two-stage trial commences. Conclusions: The probability of successful discovery of drug-specific pharmacogenomic response markers in a typical phase II study is small. The evaluation of predefined predictors using tandem two-step phase II design has the advantages of estimating response rates in both unselected and marker-selected patient populations and allows for simultaneous screening of multiple different predictors for the same drug and several distinct predictor-drug pairs in a single, parallel multiarm trial.

Reproducibility of Gene Expression Signature–Based Predictions in Replicate Experiments

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.

Thirty-Gene Pharmacogenomic Test Correlates with Residual Cancer Burden after Preoperative Chemotherapy for Breast Cancer

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 (Pearsons 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.

A human papillomavirus testing system in women with abnormal Pap results: a comparison study with follow-up biopsies.

OBJECTIVE To evaluate the efficacy of INFORM HPV using the SurePath collection method in women whose Pap tests indicated abnormal results. STUDY DESIGN Ninety-two women from the gynecology clinics at The University of Texas M.D. Anderson Cancer Center who had Pap tests and underwent follow-up biopsies were selected for the study. This included 51 women with atypical squamous cells of undetermined significance (ASCUS), 23 women with low-grade squamous intraepithelial lesion (LSIL), 15 women with high-grade squamous intraepithelial lesion (HSIL) and 3 women with negative Pap results. The INFORM HPV, an in situ hybridization assay, testing for oncogenic types of HPV was performed, and the results were compared with follow-up biopsies. RESULTS The positive rate of the INFORM HPV increased with higher grades of cytology diagnoses. The sensitivity of the INFORM HPV testing for predicting high-grade cervical intraepithelial neoplasia (CIN 2/3) also increased with higher grades of cytology diagnoses. A negative predictive value (NPV) of 94.9% and a specificity of 80.4% for predicting CIN 2/3 were observed in the ASCUS group. CONCLUSION Using SurePath Pap specimens, the INFORM HPV lacks sufficient sensitivity and NPV for predicting CIN 2/3 in women with ASCUS. Therefore, use of the test as a triage tool is limited.