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      Cell Line Derived Multi-Gene Predictor of Pathologic Response to Neoadjuvant Chemotherapy in Breast Cancer: A Validation Study on US Oncology 02-103 Clinical Trial

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          Abstract

          Background

          The purpose of this study is to assess the predictive accuracy of a multi-gene predictor of response to docetaxel, 5-fluorouracil, epirubicin and cyclophosphamide combination chemotherapy on gene expression data from patients who received these drugs as neoadjuvant treatment.

          Methods

          Tumor samples were obtained from patients with stage II-III breast cancer before starting neoadjuvant chemotherapy with four cycles of 5-fluorouracil/epirubicin/cyclophosphamide (FEC) followed by four cycles of docetaxel/capecitabine (TX) on US Oncology clinical trial 02-103. Most patients with HER-2-positive cancer also received trastuzumab (H). The chemotherapy predictor (TFEC-MGP) was developed from publicly available gene expression data of 42 breast cancer cell-lines with corresponding in vitro chemotherapy sensitivity results for the four chemotherapy drugs. No predictor was developed for treatment with trastuzumab. The predictive performance of TFEC-MGP in distinguishing cases with pathologic complete response from those with residual disease was evaluated for the FEC/TX and FEC/TX plus H group separately. The area under the receiver-operating characteristic curve (AU-ROC) was used as the metric of predictive performance. Genomic predictions were performed blinded to clinical outcome.

          Results

          The AU-ROC was 0.70 (95% CI: 0.57-0.82) for the FEC/TX group (n=66) and 0.43 (95% CI: 0.20-0.66) for the FEC/TX plus H group (n=25). Among the patients treated with FEC/TX, the AU-ROC was 0.69 (95% CI: 0.52-0.86) for estrogen receptor (ER)-negative (n=28) and it was 0.59 (95% CI: 0.36-0.82) for ER-positive cancers (n=37). ER status was not reported for one patient.

          Conclusions

          Our results indicate that the cell line derived 291-probeset genomic predictor of response to FEC/TX combination chemotherapy shows good performance in a blinded validation study, particularly in ER-negative patients.

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          Most cited references16

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          A comparison of PAM50 intrinsic subtyping with immunohistochemistry and clinical prognostic factors in tamoxifen-treated estrogen receptor-positive breast cancer.

          To compare clinical, immunohistochemical (IHC), and gene expression models of prognosis applicable to formalin-fixed, paraffin-embedded blocks in a large series of estrogen receptor (ER)-positive breast cancers from patients uniformly treated with adjuvant tamoxifen. Quantitative real-time reverse transcription-PCR (qRT-PCR) assays for 50 genes identifying intrinsic breast cancer subtypes were completed on 786 specimens linked to clinical (median follow-up, 11.7 years) and IHC [ER, progesterone receptor (PR), HER2, and Ki67] data. Performance of predefined intrinsic subtype and risk-of-relapse scores was assessed using multivariable Cox models and Kaplan-Meier analysis. Harrell's C-index was used to compare fixed models trained in independent data sets, including proliferation signatures. Despite clinical ER positivity, 10% of cases were assigned to nonluminal subtypes. qRT-PCR signatures for proliferation genes gave more prognostic information than clinical assays for hormone receptors or Ki67. In Cox models incorporating standard prognostic variables, hazard ratios for breast cancer disease-specific survival over the first 5 years of follow-up, relative to the most common luminal A subtype, are 1.99 [95% confidence interval (CI), 1.09-3.64] for luminal B, 3.65 (95% CI, 1.64-8.16) for HER2-enriched subtype, and 17.71 (95% CI, 1.71-183.33) for the basal-like subtype. For node-negative disease, PAM50 qRT-PCR-based risk assignment weighted for tumor size and proliferation identifies a group with >95% 10-year survival without chemotherapy. In node-positive disease, PAM50-based prognostic models were also superior. The PAM50 gene expression test for intrinsic biological subtype can be applied to large series of formalin-fixed, paraffin-embedded breast cancers, and gives more prognostic information than clinical factors and IHC using standard cut points. ©2010 AACR.
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            Design of a novel oral fluoropyrimidine carbamate, capecitabine, which generates 5-fluorouracil selectively in tumours by enzymes concentrated in human liver and cancer tissue.

            Capecitabine (N4-pentyloxycarbonyl-5'-deoxy-5-fluorocytidine) is a novel oral fluoropyrimidine carbamate, which is converted to 5-fluorouracil (5-FU) selectively in tumours through a cascade of three enzymes. The present study investigated tissue localisation of the three enzymes in humans, which was helpful for us to design the compound. Carboxylesterase was almost exclusively located in the liver and hepatoma, but not in other tumours and normal tissue adjacent to the tumours. Cytidine (Cyd) deaminase was located in high concentrations in the liver and various types of solid tumours. Finally, thymidine phosphorylase (dThdPase) was also more concentrated in various types of tumour tissues than in normal tissues. These unique tissue localisation patterns enabled us to design capecitabine. Oral capecitabine would pass intact through the intestinal tract, but would be converted first by carboxylesterase to 5'-deoxy-5-fluorocytidine (5'-dFCyd) in the liver, then by Cyd deaminase to 5'-deoxy-5-fluorouridine (5'-dFUrd) in the liver and tumour tissues and finally by dThdPase to 5-FU in tumours. In cultures of human cancer cell lines, the highest level of cytotoxicity was shown by 5-FU itself, followed by 5'-dFUrd. Capecitabine and 5'-dFCyd had weak cytotoxic activity only at high concentrations. The cytotoxicity of the intermediate metabolites 5'-dFCyd and 5'-dFCyd was suppressed by inhibitors of Cyd deaminase and dThdPase, respectively, indicating that these metabolites become effective only after their conversion to 5-FU. Capecitabine, which is finally converted to 5-FU by dThdPase in tumours, should be much safer and more effective than 5-FU, and this was indeed the case in the HCT116 human colon cancer and the MX-1 breast cancer xenograft models.
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              Cell line-based platforms to evaluate the therapeutic efficacy of candidate anticancer agents.

              Efforts to discover new cancer drugs and predict their clinical activity are limited by the fact that laboratory models to test drug efficacy do not faithfully recapitulate this complex disease. One important model system for evaluating candidate anticancer agents is human tumour-derived cell lines. Although cultured cancer cells can exhibit distinct properties compared with their naturally growing counterparts, recent technologies that facilitate the parallel analysis of large panels of such lines, together with genomic technologies that define their genetic constitution, have revitalized efforts to use cancer cell lines to assess the clinical utility of new investigational cancer drugs and to discover predictive biomarkers.
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                Author and article information

                Journal
                BMC Med Genomics
                BMC Med Genomics
                BMC Medical Genomics
                BioMed Central
                1755-8794
                2012
                16 November 2012
                : 5
                : 51
                Affiliations
                [1 ]Department of Product Development, Precision Therapeutics, Inc, 2516 Jane Street, Pittsburgh, PA 15203, USA
                [2 ]Department of Bioinformatics and Computational Biology, University of Texas MD Anderson Cancer Center, Houston, TX 77230, USA
                [3 ]Department of Pathology, University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd. Unit 0085, Houston, TX 77030, USA
                [4 ]Baylor Sammons Cancer Center, Texas Oncology, US Oncology, Baylor-Sammons Cancer Center, 3535 Worth St., Collins 5, Dallas, TX 75246, USA
                [5 ]Texas Oncology, US Oncology, 925 Gessner St #550, Houston, TX 77024, USA
                [6 ]Biostatistics and Medical Writing, US Oncology Research, US Oncology, The Woodlands, Woodlands, TX 77380, USA
                [7 ]Department of Breast Medical Oncology, Unit 1354, The University of Texas M. D. Anderson Cancer Center, PO Box 301439, Houston, TX 77230, USA
                Article
                1755-8794-5-51
                10.1186/1755-8794-5-51
                3536618
                23158478
                027b5111-c3e9-4c90-af3c-be85e1a37915
                Copyright ©2012 Shen et al.; licensee BioMed Central Ltd.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 19 March 2012
                : 12 November 2012
                Categories
                Research Article

                Genetics
                cell lines,breast cancer,multi-gene predictor of chemosensitivity
                Genetics
                cell lines, breast cancer, multi-gene predictor of chemosensitivity

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