Prospective comparison of clinical and genomic multivariate predictors of response to neoadjuvant chemotherapy in breast cancer.
OBJECTIVE
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.


METHODS
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.
Lee
Jae K
JK
Public Health Sciences, University of Virginia, Charlottesville, Virginia, USA.
Coutant
Charles
C
Kim
Young-Chul
YC
Qi
Yuan
Y
Theodorescu
Dan
D
Symmans
W Fraser
WF
Baggerly
Keith
K
Rouzier
Roman
R
Pusztai
Lajos
L
D000328:Adult; D000368:Aged; D000971:Antineoplastic Combined Chemotherapy Protocols / Q000627:therapeutic use*; D054316:Biomarkers, Pharmacological / Q000032:analysis*; D001943:Breast Neoplasms / Q000175:diagnosis* / Q000188:drug therapy* / Q000235:genetics / Q000473:pathology; D002277:Carcinoma / Q000175:diagnosis* / Q000188:drug therapy* / Q000235:genetics / Q000473:pathology; D003520:Cyclophosphamide / Q000008:administration & dosage; D004317:Doxorubicin / Q000008:administration & dosage; D005260:Female; D005472:Fluorouracil / Q000008:administration & dosage; D020869:Gene Expression Profiling; D015972:Gene Expression Regulation, Neoplastic; D006801:Humans; D008875:Middle Aged; D020360:Neoadjuvant Therapy; D020411:Oligonucleotide Array Sequence Analysis; D017239:Paclitaxel / Q000008:administration & dosage; D011379:Prognosis; D012680:Sensitivity and Specificity
D054316:Biomarkers, Pharmacological; D004317:Doxorubicin; D003520:Cyclophosphamide; D017239:Paclitaxel; D005472:Fluorouracil