PhD ceremony Ms. H. Hartog: The insulin-like growth factor 1 axis in prognosis and treatment of breast cancer
|Mo 14-04-2014 at 14:30
|Academiegebouw, Broerstraat 5, Groningen
PhD ceremony: Ms. H. Hartog
Dissertation: The insulin-like growth factor 1 axis in prognosis and treatment of breast cancer
Promotor(s): Prof. W.T.A. van der Graaf, Prof. H.M. Boezen
Faculty: Medical Sciences
Insulin-like growth factor-1 receptor (IGF-1R) is a tyrosine kinase receptor mediating cell growth and survival. IGF-1R signaling has been implicated in malignant behavior of tumors and drugs targeting the IGF-1R as anticancer treatment have been developed. We aimed to determine clinical indicators of IGF-1 dependency and responsiveness to IGF-1R targeted therapy in breast cancer in two large cohorts of breast cancer patients and in breast cancer cell lines.
We found that IGF-1R was frequently expressed in hormone receptor positive tumors and in those tumors related to a favorable prognosis, while IGF-1R expression was associated with a shorter disease-free survival in triple negative tumors. Overall, IGF-1 plasma levels in breast cancer patients did not show a strong relation to prognosis, however, in the subgroup of patients treated with endocrine therapy high IGF-1 levels were related to worse overall survival. We tested sensitivity of breast cancer cell lines to IGF-1R tyrosine kinase inhibition (TKI). IGF-1R TKI resulted in reduced proliferation in all cell lines but the extent of the effect was not directly related to IGF-1R expression. Both synergistic and contrary effects were seen when IGF-1R TKI was combined with several conventional systemic anti-(breast)cancer drugs.
In conclusion, our study may support approaches of combining IGF-1R-directed antibodies with endocrine therapy in breast cancer and the use of IGF-1R targeted therapy in triple negative breast tumors. However, selection of patients who could benefit from IGF-1R-targeted therapy is likely hampered by the complex interrelationships of the IGF-1R system and lack of biomarkers to predict response.