Genomic grade index is associated with response to chemotherapy in patients with breast cancer

Abstract

PURPOSE The genomic grade index (GGI) is a 97-gene measure of histological tumor grade. High GGI is associated with decreased relapse-free survival in patients receiving either endocrine or no systemic adjuvant therapy. Herein we examined whether GGI predicts pathologic response to neoadjuvant chemotherapy in patients with HER-2-normal breast cancer. METHODS Gene expression data (gene chips) was generated from fine-needle aspiration biopsies (n = 229) prospectively collected before neoadjuvant paclitaxel, fluorouracil, doxorubicin, and cyclophosphamide chemotherapy. Pathologic response was quantified using the residual cancer burden (RCB) method. The association between the GGI and pathologic response was assessed in univariate and multivariate analyses. The performance of a response predictor combining clinical variables and GGI was evaluated under cross-validation. Results Eighty-five percent of grade 1 tumors had low GGI, 89% of grade 3 tumors had high GGI, and 63% of grade 2 tumors had low GGI. Among both estrogen receptor (ER)-positive and -negative cancers, high GGI score was associated with pathologic complete response (RCB-0) or minimal residual disease (RCB-1). A multivariate model combining GGI and clinical parameters had an overall accuracy of 71%, compared with 58% for the GGI alone, for prediction of pathologic response. However, high GGI score was also associated with significantly worse distant relapse-free survival in patients with ER-positive cancer (P = .005), and was not associated with survival in patients with ER-negative cancer. CONCLUSION High GGI is associated with increased sensitivity to neoadjuvant paclitaxel plus fluorouracil, adriamycin, and cyclophosphamide chemotherapy in both ER-negative and ER-positive patients, but it remains a predictor of worse survival in ER-positive patients.

Fig 1.

Distribution of the continuous genomic grade index (GGI) within response groups defined by the residual cancer burden (RCB) for (A) estrogen receptor (ER)-positive (n = 133) and (B) ER-negative patients (n = 96). 25th and 75th percentiles are indicated by the box plot hinges and the horizontal line corresponds to the median. P values are derived from an unequal variance t-test of GGI in pathologic complete response (pCR) or RCB-I as compared to RCB-II or RCB-III groups.

Fig 2.

Cross-validated receiver operating characteristic (ROC) curves for the multivariate logistic regression models for chemotherapy response (pathologic complete response or residual cancer burden [RCB]-I) shown in Appendix Table A1. The area under the ROC curve (AUC) for the model that included only the clinical covariates (age at diagnosis, estrogen receptor status, nodal status, histologic grade, and tumor stage) was 0.714 (95% CI, 0.685 to 0.743), whereas that of the full model combining clinical covariates and continuous genomic grade index (GGI) was 0.735 (95% CI, 0.702 to 0.768). Box plots show for a series of false positive rates the distribution of true-positive rates estimated under cross validation.

Fig 3.

Kaplan-Meier curves for distant relapse-free survival after neoadjuvant paclitaxel plus fluorouracil, adriamycin, and cyclophosphamide by genomic grade (GG) risk group: (A) estrogen receptor (ER)-positive patients; (B) ER-negative patients (P values are derived from the log-rank test).

Fig A1.

Continuous genomic grade index (GGI) plotted against residual cancer burden (RCB) scores for estrogen receptor (ER)-positive and ER-negative patients separately.

Fig A2.

Continuous Ki67 plotted against residual cancer burden (RCB) scores for estrogen receptor (ER)-positive and ER-negative patients separately.

Fig A3.

Continuous genomic grade index plotted against Ki67 for estrogen (ER)-positive and ER-negative patients separately. RCB, residual cancer burden.