Anti-RPLP0 monoclonal antibody Made to order

Treatment of breast cancer is complex and challenging due to the heterogeneity of the disease. To avoid significant toxicity and adverse side-effects of chemotherapy in patients who respond poorly, biomarkers predicting therapeutic response are essential. This study has utilized a proteomic approach integrating 2D-DIGE, LC-MS/MS, and bioinformatics to analyze the proteome of breast cancer (ZR-75-1 and MDA-MB-231) and breast epithelial (MCF-10A) cell lines induced to undergo apoptosis using a combination of doxorubicin and TRAIL administered in sequence (Dox-TRAIL). Apoptosis induction was confirmed using a caspase-3 activity assay. Comparative proteomic analysis between whole cell lysates of Dox-TRAIL and control samples revealed 56 differentially expressed spots (>= 2-fold change and p < 0.05) common to at least two cell lines. Of these, 19 proteins were identified yielding 11 unique protein identities: CFL1, EIF5A, HNRNPIC, KRT8, KRT18, LMNA, MYH9, NACA, RPLP0, RPLP2, and RAD23B. A subset of the identified proteins was validated by selected reaction monitoring (SRM) and Western blotting. Pathway analysis revealed that the differentially abundant proteins were associated with cell death, cellular organization, integrin-linked kinase signaling, and actin cytoskeleton signaling pathways. The 2D-DIGE analysis has yielded candidate biomarkers of response to treatment in breast cancer cell models. Their clinical utility will depend on validation using patient breast biopsies pre- and post-treatment with anticancer drugs.

Clinically, Akt overexpression has been associated with tamoxifen resistance, and multiple in vitro breast cancer models of tamoxifen resistance have been developed. In order to study the mechanism of this tamoxifen resistance, differential gene expression studies have been performed utilizing quantitative reverse transcription-polymerase chain reaction (RT-qPCR). Since accurate data normalization requires the use of a stable reference gene, the goal of this study was to identify the most stable reference gene for RT-qPCR (from a panel of putative housekeeping genes) that remains unaltered despite estrogen or tamoxifen treatment or stable overexpression of active Akt. Gene expression of nine candidate genes was determined in parental and Akt overexpressing MCF-7 breast cancer cells treated with estrogen, tamoxifen, or vehicle, and gene stability was analyzed using two different statistical models. Based on our results, we suggest RPL13A as suitable internal reference gene that is both stable and remains unaltered in MCF-7 cells regardless of estrogen or tamoxifen treatment or Akt overexpression. We also validated that expression levels for RPL13A, as well as RPLP0 (another member of the RPL protein family), remain unaltered after estrogen and tamoxifen treatment in the ER positive ZR-75-1 cell line and ER negative MDA-MB-468 breast cancer cell line. Both RPL13A and RPLP0 levels were also stable in normal and tumor mammary tissue from Her2 overexpressing mice. In addition, our work emphasizes the importance of a preliminary study to validate each reference gene that will be used for RT-qPCR. (C) 2011 Elsevier Ltd. All rights reserved.