Combination of immunosuppressive drugs leaves specific “fingerprint” on gene expression in vitro

References

• Hernandez-Fuentes, M.P.; Warrens, A.N.; Lechler, R.I. Immunologic monitoring. Immunol Rev. 2003, 196, 247–264.
   PubMed Web of Science ®Google Scholar
• Barten, M.J.; Streit, F.; Boeger, M.et al. Synergistic effects of sirolimus with cyclosporine and tacrolimus: analysis of immunosuppression on lymphocyte proliferation and activation in rat whole blood. Transplantation. 2004, 77, 1154–1162.
   PubMed Web of Science ®Google Scholar
• Flores, M.G.; Zhang, S.; Ha, A.et al. In vitro evaluation of the effects of candidate immunosuppressive drugs: Flow cytometry and quantitative real-time PCR as two independent and correlated read-outs. J Immunol Methods. 2004, 289, 123–135.
   PubMed Web of Science ®Google Scholar
• Ellisen, L.W.; Palmer, R.E.; Maki, R.G.et al. Cascades of transcriptional induction during human lymphocyte activation. Eur J Cell Biol. 2001, 0, 321–328.
   Google Scholar
• Fujino, M.; Kitazawa, Y.; Kawasaki, M.et al. Differences in lymphocyte gene expression between tolerant and syngeneic liver grafted rats. Liver Transpl. 2004, 10, 379–391.
   PubMed Web of Science ®Google Scholar
• Erickson, L.M.; Pan, F.; Ebbs, A.; Kobayashi, M.; Jiang, H. Microarray-based gene expression profiles of allograft rejection and immunosuppression in the rat heart transplantation model. Transplantation. 2003, 76, 582–588.
   PubMed Web of Science ®Google Scholar
• Sarwal, M.; Chua, M.S.; Kambham, N.et al. Molecular heterogeneity in acute renal allograft rejection identified by DNA microarray profiling. N Engl J Med. 2003, 349, 125–138.
   PubMed Web of Science ®Google Scholar
• Donauer, J.; Rumberger, B.; Klein, M.et al. Expression profiling on chronically rejected transplant kidneys. Transplantation. 2003, 76, 539–547.
   PubMed Web of Science ®Google Scholar
• Lamb, J.; Crawford, E.D.; Peck, D.et al. The connectivity map: Using gene-expression signatures to connect small molecules, genes, and disease. Science. 2006, 313, 1929–35.
   PubMed Web of Science ®Google Scholar
• Boldrick, J.C.; Alizadeh, A.A.; Diehn, M.et al. Stereotyped and specific gene expression programs in human innate immune responses to bacteria. Proc Natl Acad Sci USA. 2002, 99, 972–977.
   PubMed Web of Science ®Google Scholar
• Khanna, A.K. Mechanism of the combination immunosuppressive effects of rapamycin with either cyclosporine or tacrolimus. Transplantation. 2000, 70, 690–694.
   PubMed Web of Science ®Google Scholar
• Barten, M.J.; Gummert, J.F.; van Gelder, T.; Shorthouse, R.; Morris, R.E. Flow cytometric quantitation of calcium-dependent and -independent mitogen-stimulation of T cell functions in whole blood: Inhibition by immunosuppressive drugs in vitro. J Immunol Methods. 2001, 253, 95–112.
   PubMed Web of Science ®Google Scholar
• Wright, D.C.; Deol, H.S.; Tuch, B.E. A comparison of the sensitivity of pig and human peripheral blood mononuclear cells to the antiproliferative effects of traditional and newer immunosuppressive agents. Transpl Immunol. 1999, 7, 141–147.
   PubMed Web of Science ®Google Scholar
• Eisen, M.B.; Brown, P.O. DNA arrays for analysis of gene expression. Methods Enzymol. 1999, 303, 179–205.
   PubMed Web of Science ®Google Scholar
• Brazma, A.; Hingamp, P.; Quackenbush, J.et al. Minimum information about a microarray experiment (MIAME)-toward standards for microarray data. Nat Genet. 2001, 29, 365–371.
   PubMed Web of Science ®Google Scholar
• Workman, C.; Jensen, L.J.; Jarmer, H.et al. A new non-linear normalization method for reducing variability in DNA microarray experiments. Genome Biol. 2002, 0023, research0048.
   Google Scholar
• Benjamini, Y.; Drai, D.; Elmer, G.; Kafkafi, N.; Golani, I. Controlling the false discovery rate in behavior genetics research. Behav Brain Res. 2001, 125, 279–284.
   PubMed Web of Science ®Google Scholar
• Kaufman, L.; Rousseeuw, P. Finding Groups in Data: An Introduction to Cluster Analysis. John Wiley Sciences, New York, 1990.
   Google Scholar
• Schroppel, B.; Zhang, N.; Chen, P. et al. Murphy, Differential expression of chemokines and chemokine receptors in murine isl et allografts: The role of CCR2 and CCR5 signaling pathways. J Am Soc Nephrol. 2004, 15, 1853–1861.
   PubMed Web of Science ®Google Scholar
• Dudley, J.; Truman, C.; McGraw, M.; Tizard, J.; Haque, G.; Bradley, B. Estimation of individual sensitivity to cyclosporin in children awaiting renal transplantation. Nephrol Dial Transplant. 2003, 18, 403–410.
   PubMed Web of Science ®Google Scholar
• Cristillo, A.D.; Bierer, B.E. Identification of novel targets of immunosuppressive agents by cDNA-based microarray analysis. J Biol Chem. 2002, 277, 4465–4476.
   PubMed Web of Science ®Google Scholar
• Libetta, C.; Sepe, V.; Zucchi, M.et al. The effect of sirolimus- or cyclosporine-based immunosuppression effects on T-cell subsets in vivo. Kidney Int. 2007, 72, 114–20.
   PubMed Web of Science ®Google Scholar
• Jin, S.; Mathis, A.S.; Rosenblatt, J.et al. Insights into cyclosporine A-induced atherosclerotic risk in transplant recipients: Macrophage scavenger receptor regulation. Transplantation. 2004, 77, 497–504.
   PubMedGoogle Scholar
• Jin, S.; Mathis, A.S.; Gioia, K.et al. Effect of tacrolimus on the expression of macrophage scavenger and nuclear hormone receptors in THP-1-derived human macrophages. Transplantation. 2004, 77, 1281–1287.
   PubMed Web of Science ®Google Scholar
• Castro, C.; Campistol, J.M.; Sancho, D.; Sanchez-Madrid, F.; Casals, E.; Andres, V. Rapamycin attenuates atherosclerosis induced by dietary cholesterol in apolipoprotein-deficient mice through a p27 Kip1-independent pathway. Atherosclerosis. 2004, 172, 31–38.
   PubMed Web of Science ®Google Scholar
• Mathis, A.S.; Jin, S.; Friedman, G.S.; Peng, F.; Carl, S.M.; Knipp, G.T. The pharmacodynamic effects of sirolimus and sirolimus-calcineurin inhibitor combinations on macrophage scavenger and nuclear hormone receptors. J Pharm Sci. 2007, 96, 209–22.
   PubMed Web of Science ®Google Scholar