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

Hess, Kenneth R.; Anderson, K.; Symmans, W. Fraser; Valero, Vicente; Ibrahim, Nuhad K.; Mejia, Jaime; Booser, Daniel J.; Theriault, Richard L.; Buzdar, Aman U.; Dempsey, Peter J.; Rouzier, Roman; Sneige, Nour; Ross, Jeffrey S.; Vidaurre, Tatiana; Gómez, Henry L.; Hortobágyi, Gabriel N.; Pusztai, Lajos

doi:10.1200/jco.2006.05.6861

Cited by 620 publications

(600 citation statements)

References 22 publications

(7 reference statements)

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“…Conversely, FNA can collect a small sample size, approximately 30% of samples reportedly are not evaluable, and the success rate reported by Hess et al was approximately 70%. 12 However, those authors used the oligo-dT method for RNA amplification, which requires a larger amount of RNA than the random primer method that we used in the current study. Thus, the success rates of the 2 biopsy methods cannot be compared because of the different protocols for RNA amplification.…”

Section: Discussionmentioning

confidence: 97%

“…Hess et al 12 reported that 31-gene classifier analysis using FNA samples was useful for predicting the response to P-FAC. The NPV (96%) and PPV (52%) of that 31-gene classifier were very similar to those obtained with the 70-gene classifier in our study using core-needle samples.…”

Section: Discussionmentioning

confidence: 99%

“…This association also was reported by Hess et al in their 31-gene classifier. 12 The genes that were selected for the 70-gene classifier and the 31-gene classifier do not overlap except for ERBB4. The reason for such a different gene selection may be attributable to differences in the tumor sampling method (FNA vs core-needle biopsy), the platform for DNA microarray (U133 A vs U133 plus 2.0), and the statistical method.…”

Section: Discussionmentioning

confidence: 99%

“…10 In addition, sequential taxane and anthracycline-containing regimes are used most commonly in the neoadjuvant setting. Thus, Ayers et al 11 tried to identify a 74-gene signature associated with pCR to sequential paclitaxel plus 5-fluorouracil (5-FU)/doxorubicin/cyclophosphamide (FAC), and Hess et al 12 reported using a 31-gene classifier as a predictor of pCR to the same regimen with similar diagnostic accuracy.…”

mentioning

confidence: 99%

“…In the studies by Ayers et al 11 and Hess et al, 12 tumor samples were obtained with fine-needle aspiration (FNA) before patients received neoadjuvant chemotherapy. Because, currently, patients usually undergo core-needle tumor biopsy (eg, Mammotome; HH Ethicon Endosurgery, Johnson and Johnson Company, Langhorne, Penn) before they receive neoadjuvant chemotherapy, and a sufficient sample volume for the gene expression assay is easily obtainable, we believe that core-needle samples constitute a better source for the assay than FNA samples.…”

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Prediction of pathologic complete response to sequential paclitaxel and 5-fluorouracil/epirubicin/cyclophosphamide therapy using a 70-gene classifier for breast cancers

Naoi

Kishi

Tanei

et al. 2011

Cancer

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BACKGROUND. Sequential administration of paclitaxel plus combined fluorouracil, epirubicin, and cyclophosphamide (P-FEC) is 1 of the most common neoadjuvant chemotherapies for patients with primary breast cancer and produces pathologic complete response (pCR) rates of 20% to 30%. However, a predictor of pCR to this chemotherapy has yet to be developed. The authors developed such a predictor by using a proprietary DNA microarray for gene expression analysis of breast tumor tissues. METHODS. Tumor samples were obtained from 84 patients with breast cancer by core-needle biopsy before the patients received P-FEC, and the gene expression profile was analyzed in those samples to construct a classifier for predicting pCR to P-FEC. In addition, the authors analyzed the gene expression profile of tumor tissues that were obtained at surgery from 105 patients with lymph node-negative and estrogen receptor-positive breast cancer who received adjuvant hormone therapy alone to determine the prognostic significance of the classifier. RESULTS. The 70-gene classifier for predicting pCR to P-FEC was constructed by using the training set (n ¼ 50) and subsequently was validated successfully in the validation set (n ¼ 34), revealing high sensitivity (88%; 95% confidence interval [CI], 47%-100%) and high negative predictive value (93%; 95% CI, 68%-100%). Specificity and positive predictive value were 54% (95% CI, 33%-73%) and 37% (95% CI, 16%-62%), respectively. Among the various parameters (estrogen receptor, progesterone receptor, human epidermal growth factor receptor 2, and Ki-67 status, etc), the 70-gene classifier had the strongest association with pCR (P ¼ .015). In an additional study, genetically assumed complete responders were associated significantly (P ¼ .047) with a poor prognosis. CONCLUSIONS. The 70-gene classifier that was constructed for predicting pCR to P-FEC for breast tumors was successful, with high sensitivity and high negative predictive value. The classifier also appeared to be useful for predicting the prognosis of patients with lymph node-negative and estrogen receptor-positive breast cancer who receive adjuvant hormone therapy alone. Cancer 2011;117:3682-

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Section: Discussionmentioning

confidence: 97%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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Prediction of pathologic complete response to sequential paclitaxel and 5-fluorouracil/epirubicin/cyclophosphamide therapy using a 70-gene classifier for breast cancers

Naoi

Kishi

Tanei

et al. 2011

Cancer

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A Genomic Predictor of Response and Survival Following Taxane-Anthracycline Chemotherapy for Invasive Breast Cancer

Hatzis

Pusztai

Valero

et al. 2011

JAMA

559

624

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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.

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Journal De La Société Française De Statistique

Caussinus

Falguerolles

2005

Encyclopedia of Statistical Sciences

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

Cited by 620 publications

References 22 publications

Prediction of pathologic complete response to sequential paclitaxel and 5-fluorouracil/epirubicin/cyclophosphamide therapy using a 70-gene classifier for breast cancers

Prediction of pathologic complete response to sequential paclitaxel and 5-fluorouracil/epirubicin/cyclophosphamide therapy using a 70-gene classifier for breast cancers

A Genomic Predictor of Response and Survival Following Taxane-Anthracycline Chemotherapy for Invasive Breast Cancer

Journal De La Société Française De Statistique

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