The purpose of this study was to analyze global gene expression changes in serial tumor core biopsy specimens taken during neoadjuvant chemotherapy for primary breast cancer.
Core biopsy specimens from tumors were obtained before treatment and 24 and/or 48 hours after treatment from 21 women who were beginning chemotherapy for breast cancer. RNA was extracted, and radiolabeled complementary DNA was synthesized. The complementary DNA probes were hybridized to high-density microarray membranes that contained more than 25,000 human sequence clones. Hierarchical cluster analysis was used to compare the degree of similarity between expression profiles.
Twenty-five (45%) of the 56 available core specimens yielded sufficient quantity and quality RNA for microarray analysis. Microarray profiles were performed only on samples from patients with pretreatment and posttreatment specimens, resulting in serial data sets for five patients (14 specimens). The serial samples from individual patients clustered more closely than the samples taken from different patients. Analyses of the variance of individual gene expression showed that there were significantly fewer genes with fivefold differences in expression in an individual tumor at different times (average, 359 genes) versus pre-treatment samples of different tumors (average, 732 genes). Patients with a good pathological response to treatment had gene patterns that clustered distinctly from those of poor responders. Significant transcriptional response occurred in all patients during therapy. Surprisingly, all patients had different genes change after chemotherapy, with no single gene having a significant expression change in all five patients.
This is the first report to show global gene expression changes during chemotherapy in a human solid tumor. Comprehensive gene expression profiles of more than 25,000 genes can be obtained from core biopsy specimens. A remarkable diversity in transcriptional response was observed for individual cases. Further data are needed to determine whether gene profiling can predict response to chemotherapy.
aDepartment of Radiation Oncology, The University of Texas M.D. Anderson Cancer Center, Houston, Texas
bDepartment of Biostatistics, The University of Texas M.D. Anderson Cancer Center, Houston, Texas
cMillennium Pharmaceuticals, Cambridge, Massachusetts.
dDepartment of Pathology, The University of Texas M.D. Anderson Cancer Center, Houston, Texas
eDepartment of Surgical Oncology, The University of Texas M.D. Anderson Cancer Center, Houston, Texas
fDepartment of Breast Medical Oncology, The University of Texas M.D. Anderson Cancer Center, Houston, Texas
Reprint requests: Thomas A. Buchholz, MD, Department of Radiation Oncology, The University of Texas M. D. Anderson Cancer Center, Box 97, 1515 Holcombe Blvd., Houston, TX 77030.
The author or one or more of the authors have received or will receive benefits for personal or professional use from a commercial party related directly or indirectly to the subject of this article. In addition, benefits have been or will be directed to a research fund, foundation, educational institution, or other nonprofit organization with which one or more of the authors is associated. This work was supported in part by National Cancer Institute Department of Health and Human Services grant nos. CA16672 and T32CA77050. Dr. Buchholz is supported by grant no. BC980154, a USAMRMC Breast Cancer Research Program Career Development Award. Dr Pusztai is supported by a research grant from Millennium Pharmaceuticals.
Received on June 28, 2002; accepted for publication August 1, 2002.