Molecular characterization of radical prostatectomy specimens after systemic therapy may identify a gene expression profile for resistance to therapy. This study assessed tumor cells from patients with prostate cancer participating in a phase II neoadjuvant docetaxel and androgen deprivation trial to identify mediators of resistance. Transcriptional level of 93 genes from a docetaxel-resistant prostate cancer cell lines microarray study was analyzed by TaqMan low-density arrays in tumors from patients with high-risk localized prostate cancer (36 surgically treated, 28 with neoadjuvant docetaxel þ androgen deprivation). Gene expression was compared between groups and correlated with clinical outcome. VIM, AR and RELA were validated by immunohistochemistry. CD44 and ZEB1 expression was tested by immunofluorescence in cells and tumor samples. Parental and docetaxel-resistant castration-resistant prostate cancer cell lines were tested for epithelial-to-mesenchymal transition (EMT) markers before and after docetaxel exposure. Reversion of EMT phenotype was investigated as a docetaxel resistance reversion strategy. Expression of 63 (67.7%) genes differed between groups (P < 0.05), including genes related to androgen receptor, NF-kB transcription factor, and EMT. Increased expression of EMT markers correlated with radiologic relapse. Docetaxel-resistant cells had increased EMT and stem-like cell markers expression. ZEB1 siRNA transfection reverted docetaxel resistance and reduced CD44 expression in DU-145R and PC-3R. Before docetaxel exposure, a selected CD44 þ subpopulation of PC-3 cells exhibited EMT phenotype and intrinsic docetaxel resistance; ZEB1/CD44 þ subpopulations were found in tumor cell lines and primary tumors; this correlated with aggressive clinical behavior. This study identifies genes potentially related to chemotherapy resistance and supports evidence of the EMT role in docetaxel resistance and adverse clinical behavior in early prostate cancer. Mol Cancer Ther; 13(5); 1270-84. Ó2014 AACR.

Docetaxel-based chemotherapy is the standard first-line therapy in metastatic castration-resistant prostate cancer (CRPC). However, most patients eventually develop resistance to this treatment. In this study, we aimed to identify key molecular genes and networks associated with docetaxel resistance in two models of docetaxelresistant CRPC cell lines and to test for the most differentially expressed genes in tumor samples from patients with CRPC. DU-145 and PC-3 cells were converted to docetaxel-resistant cells, DU-145R and PC-3R, respectively. Whole-genome arrays were used to compare global gene expression between these four cell lines. Results showed differential expression of 243 genes (P < 0.05, Bonferroni-adjusted P values and log ratio > 1.2) that were common to DU-145R and PC-3R cells. These genes were involved in cell processes like growth, development, death, proliferation, movement, and gene expression. Genes and networks commonly deregulated in both DU-145R and PC-3R cells were studied by Ingenuity Pathways Analysis. Exposing parental cells to TGFB1 increased their survival in the presence of docetaxel, suggesting a role of the TGF-b superfamily in conferring drug resistance. Changes in expression of 18 selected genes were validated by real-time quantitative reverse transcriptase PCR in all four cell lines and tested in a set of 11 FFPE and five optimal cutting temperature tumor samples. Analysis in patients showed a noteworthy downexpression of CDH1 and IFIH1, among others, in docetaxel-resistant tumors. This exploratory analysis provides information about potential gene and network involvement in docetaxel resistance in CRPC. Further clinical validation of these results is needed to develop targeted therapies in patients with CRPC that can circumvent such resistance to treatment.

Background Both clinical and genomic data independently predict survival and treatment response in early-stage HER2-positive breast cancer. Here we present the development and validation of a new HER2DX risk score, and a new HER2DX pathological complete response (pCR) score, both based on a 27-gene expression plus clinical featurebased classifier.Methods HER2DX is a supervised learning algorithm incorporating tumour size, nodal staging, and 4 gene expression signatures tracking immune infiltration, tumour cell proliferation, luminal differentiation, and the expression of the HER2 amplicon, into a single score. 434 HER2-positive tumours from the Short-HER trial were used to train a prognostic risk model; 268 cases from an independent cohort were used to verify the accuracy of the HER2DX risk score. In addition, 116 cases treated with neoadjuvant anti-HER2-based chemotherapy were used to train a predictive model of pathological complete response (pCR); two independent cohorts of 91 and 67 cases were used to verify the accuracy of the HER2DX pCR likelihood score. Five publicly available independent datasets with >1,000 patients with early-stage HER2-positive disease were also analysed.Findings In Short-HER, HER2DX variables were associated with good risk outcomes (i.e., immune, and luminal) and poor risk outcomes (i.e., proliferation, and tumour and nodal staging). In an independent cohort, continuous HER2DX risk score was significantly associated with disease-free survival (DFS) (p=0¢002); the 5-year DFS in the low-risk group was 97¢4% (94¢4-100¢0%). For the neoadjuvant pCR predictor training cohort, HER2DX variables were associated

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