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In the research group "Experimental Pathology" various aspects of therapy resistance of cancer cells are investigated. For that approach multiple in vitro models were established and characterized on different cellular levels by molecular biological approached including "-omics" technologies. Findings are validated in specimens prepared from cancer patients. Vice versa, also factors identified in tissue samples from patients are characterized in in vitro models. The findings are used for development of improved diagnostics for prediction of clinical outcome of a given therapy. Furthermore, strategies are developed for reversal of therapy resistance. These strategies include the application of new synthesized conventional pharmacological active small molecules as well as experimental strategies using RNA-based approaches, e.g. RNA interference (RNAi) technology. Furthermore, improved strategies for delivery of therapeutic RNAi effectors are under investigation. These strategies include therapeutic non-pathogen microorganisms and oncolytic viruses.
- DFG: "Development of symmetric MDR modulators and evaluation of their efficacy in cellular systems"
- BMBF: "Identification and characterization of markers associated with oncolytic virus therapy"
- Deutsche Krebshilfe: "Functional investigation of new genes identified to be associated with hereditary breast cancer"
- Industry: "Characterisation of ZK-EPO in drug-sensitive and drug-resistant cancer cells"
- Industry: "Development of a microbial system for administration of therapeutic RNA molecules in drug-resistant cancer cells"
- Industry: "Development of peptide-linked therapeutic RNAs for specific treatment of drug-resistant cancer cells"
- Authors:Wichert, A., Stege, A., Midorikawa, Y., Holm, P.S., and Lage, HJournal:Oncogene Year:2004; Volume:23:Pages:945-955.
- Authors:Kowalski, P., Surowiak, P., and Lage, H
Journal:Mol Ther Year:2005; Volume:11:Pages:508-522.
Title:Reversal of different drug-resistant phenotypes by an autocatalytic multitarget multiribozyme directed against the transcripts of the ABC-transporters MDR1/P-gp, MRP2, and BCRP
- Authors:Materna, V., Liedert, B., Thomale, J., and Lage, H
Journal:Int J Cancer Year:2005; Volume:115:Pages:393-402.
Title:Protection of platinum-DNA adduct formation and reversal of cisplatin resistance by anti-MRP2 hammerhead ribozymes in human cancer cells
- Authors:Lage, H
Journal:Curr Drug Targets Year:2006; Volume:7:Pages:813-821.
Title:MDR1/P-glycoprotein (ABCB1) as target for RNA interference-mediated reversal of multidrug resistance
- Authors:Surowiak, P., Materna, V., Kaplenko, I., Spaczynski, M., Dolinska-Krajewska, B., Gebarowska, E., Dietel, M., Zabel, M., and Lage, H
Journal:Clin Cancer Res Year:2006; Volume:12:Pages:7149-7158.
Title:ABCC2 (MRP2, cMOAT) can be localized in the nuclear membrane of ovarian carcinomas and correlates with resistance to cisplatin and clinical outcome
- Authors:Hoffmann, J., Vitale, I., Buchmann, B., Galluzzi, L., Schwede, W., Senovilla, L., Skuballa, W., Vivet, S., Lichtner, R.B., Vicencio, J.M., Panaretakis, T., Siemeister, G., Lage, H., Nanty, L., Hammer, S., Mittelstaedt, K., Winsel, S., Eschenbrenner, J., Castedo, M., Demarche, C., Klar, U., and Kroemer, G
Journal:Cancer Res Year:2008; Volume:68:Pages:5301-5308.
Title:Improved cellular pharmacokinetics and pharmacodynamics underlie the wide anticancer activity of sagopilone
- Authors:Lage, H.Journal:Mol Life Sci Year:2008; Volume:65 :Pages:3145-3167.
- Authors:Stein, U., Walther, W., Stege, A., Kaszubiak, A., Fichtner, I., and Lage, H
Journal:Mol Ther Year:2008; Volume:16:Pages:178-186.
Title:Complete in vivo reversal of the multidrug resistance (MDR) phenotype by jet-injection of anti-MDR1 short hairpin RNA-encoding plasmid DNA
- Authors:Denkert, C., Budczies, J., Darb-Esfahani, S., Györffy, B., Sehouli, J., Könsgen, D., Zeillinger, R., Weichert, W., Noske, A., Buckendahl, A.-C., Müller, B.M., Dietel, M., and Lage, H
Journal:J Path Year:2009; Volume:218:Pages:273-280.
Title:A prognostic gene expression index in ovarian cancer – validation across different independent datasets