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  4. Structural and quantitative characterisation of canine RAGE gene transcripts and evaluation of canine HMG genes and proteins for the establishment of therapeutic strategies
 
Zitierlink URN
https://nbn-resolving.de/urn:nbn:de:gbv:46-00102304-13

Structural and quantitative characterisation of canine RAGE gene transcripts and evaluation of canine HMG genes and proteins for the establishment of therapeutic strategies

Veröffentlichungsdatum
2011-09-30
Autoren
Sterenczak, Katharina  
Betreuer
Bullerdiek, Jörn  
Gutachter
Nolte, Ingo  
Zusammenfassung
Cancer is the leading cause of death in economic strong countries and a large number of in vivo and in vitro models of human cancer were established until today. Thereby the dog has attracted scientific interest as neoplasias seen in dogs share many characteristics with their human counterparts. The aim of this thesis was the analysis of the molecular structure and/or expression pattern of cancer associated genes and proteins in canine neoplasias including the receptor RAGE and members of the HMG family. The results showed high similarities between the canine and human genes analysed and a valuable cell line based in vivo model of canine prostate cancer was established. The results clearly show that therapies targeting the RAGE/HMGB1 complex or HMGA expression can be of great value for the establishment of novel therapeutic strategies targeting canine neoplasias. Due to the similarities that were found between humans and dogs in cancer, in terms of transferability, established therapies in dogs would be suitable as preclinical approaches in human neoplasias.
Schlagwörter
canine cancer

; 

receptor RAGE

; 

HMG family members

; 

expression analyses

; 

therapy

; 

in vivo model prostate cancer
Institution
Universität Bremen  
Fachbereich
Fachbereich 02: Biologie/Chemie (FB 02)  
Dokumenttyp
Dissertation
Zweitveröffentlichung
Nein
Sprache
Englisch
Dateien
Lade...
Vorschaubild
Name

00102304-1.pdf

Size

5.58 MB

Format

Adobe PDF

Checksum

(MD5):758d848a2f5902c72e0e63389dbd19be

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