Evaluation of a 30-Gene Paclitaxel, Fluorouracil, Doxorubicin, and Cyclophosphamide Chemotherapy Response Predictor in a Multicenter Randomized Trial in Breast Cancer

Abstract

Purpose We examined in a prospective, randomized, international clinical trial the performance of a previously defined 30-gene predictor (DLDA-30) of pathologic complete response (pCR) to preoperative weekly paclitaxel and fluorouracil, doxorubicin, cyclophosphamide (T/FAC) chemotherapy, and assessed if DLDA-30 also predicts increased sensitivity to FAC-only chemotherapy. We compared the pCR rates after T/FAC versus FAC×6 preoperative chemotherapy. We also performed an exploratory analysis to identify novel candidate genes that differentially predict response in the two treatment arms. Experimental Design 273 patients were randomly assigned to receive either weekly paclitaxel × 12 followed by FAC × 4 (T/FAC, n=138), or FAC × 6 (n=135) neoadjuvant chemotherapy. All patients underwent a pretreatment FNA biopsy of the tumor for gene expression profiling and treatment response prediction. Results The pCR rates were 19% and 9% in the T/FAC and FAC arms, respectively (p<0.05). In the T/FAC arm, the positive predictive value (PPV) of the genomic predictor was 38% (95%CI:21–56%), the negative predictive value (NPV) 88% (CI:77–95%) and the AUC 0.711. In the FAC arm, the PPV was 9% (CI:1–29%) and the AUC 0.584. This suggests that the genomic predictor may have regimen-specificity. Its performance was similar to a clinical variable-based predictor nomogram. Conclusions Gene expression profiling for prospective response prediction was feasible in this international trial. The 30-gene predictor can identify patients with greater than average sensitivity to T/FAC chemotherapy. However, it captured molecular equivalents of clinical phenotype. Next generation predictive markers will need to be developed separately for different molecular subsets of breast cancers.

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

“…The diagnostic accuracy of the clinical nomogram and genetic predictor reportedly is similar. 22 Thus, a comparison of our 70-gene classifier with the clinical nomogram may be very important and needs to be done in future.…”

Impact of chemotactic factors and receptors on the cancer immune infiltrate: a bioinformatics study revealing homogeneity and heterogeneity among patient cohorts

“…Five different datasets were included for several major cancer types, in particular breast carcinoma (TCGA consortium), 31–34 colorectal carcinoma (http://www.intgen.org or TCGA consortium), 35,36 non-small cell lung carcinoma (TCGA consortium) 37–40 and melanoma, 41–45 to study the correlation between the expression level of metagenes indicating the presence of immune cell types and a variety of chemotactic factors and receptors. An extra dataset concerning breast carcinoma 46 was used for studying expression variability and treatment response.…”

“…We explored the link between chemotactic factors/receptors and response to treatment in the four out of the five Breast Carcinoma datasets for which the treatment response was annotated (as pathological complete response or simple response, see Table 2) after neo-adjuvant chemotherapy: Bonnefoi, 32 Hatzis, 33  Tabchy, 34 and Korde. 46 We also included the METABRIC dataset 81 in this analysis, because we had access to the information whether patients were alive or deceased, a status that is related to disease prognosis and treatment response.…”

Plasma and tissue proteomic prognostic factors of response in primary breast cancer patients receiving neoadjuvant chemotherapy

“…Similarly, the pCR rate was higher in triple-negative tumors (28) and in ductular than in lobular cancer (29). Several molecular signatures are being tested in the neoadjuvant setting (30)(31)(32)(33). However, the benefit of using genetic predictors over usual pathological biomarkers is not clear.…”