TY - JOUR

T1 - Angiotensinogen and HLA class II predict bevacizumab response in recurrent glioblastoma patients

AU - Urup, Thomas

AU - Michaelsen, Signe Regner

AU - Olsen, Lars Rønn

AU - Toft, Anders

AU - Christensen, Ib Jarle

AU - Grunnet, Kirsten

AU - Winther, Ole

AU - Broholm, Helle

AU - Kosteljanetz, Michael

AU - Issazadeh-Navikas, Shohreh

AU - Poulsen, Hans Skovgaard

AU - Lassen, Ulrik Niels

PY - 2016/10

Y1 - 2016/10

N2 - BackgroundBevacizumab combination therapy is among the most frequently used treatments in recurrent glioblastoma and patients who achieve response to bevacizumab have improved survival as well as quality of life. Accordingly, the aim of this study was to identify predictive biomarkers for bevacizumab response in recurrent glioblastoma patients.MethodsThe study included a total of 82 recurrent glioblastoma patients treated with bevacizumab combination therapy whom were both response and biomarker evaluable. Gene expression of tumor tissue was analyzed by using a customized NanoString platform covering 800 genes. Candidate gene predictors associated with response were analyzed by multivariate logistic and Cox regression analysis.ResultsTwo genes were independently associated with response: Low expression of angiotensinogen (2-fold decrease in AGT; OR = 2.44; 95% CI: 1.45–4.17; P = 0.0009) and high expression of a HLA class II gene (2-fold increase in HLA-DQA1; OR = 1.22; 95% CI: 1.01–1.47; P = 0.04). These two genes were included in a model that is able predict response to bevacizumab combination therapy in clinical practice. When stratified for a validated prognostic index, the predictive model for response was significantly associated with improved overall survival.ConclusionTwo genes (low angiotensinogen and high HLA-class II expression) were predictive for bevacizumab response and were included in a predictive model for response. This model can be used in clinical practice to identify patients who will benefit from bevacizumab combination therapy.

AB - BackgroundBevacizumab combination therapy is among the most frequently used treatments in recurrent glioblastoma and patients who achieve response to bevacizumab have improved survival as well as quality of life. Accordingly, the aim of this study was to identify predictive biomarkers for bevacizumab response in recurrent glioblastoma patients.MethodsThe study included a total of 82 recurrent glioblastoma patients treated with bevacizumab combination therapy whom were both response and biomarker evaluable. Gene expression of tumor tissue was analyzed by using a customized NanoString platform covering 800 genes. Candidate gene predictors associated with response were analyzed by multivariate logistic and Cox regression analysis.ResultsTwo genes were independently associated with response: Low expression of angiotensinogen (2-fold decrease in AGT; OR = 2.44; 95% CI: 1.45–4.17; P = 0.0009) and high expression of a HLA class II gene (2-fold increase in HLA-DQA1; OR = 1.22; 95% CI: 1.01–1.47; P = 0.04). These two genes were included in a model that is able predict response to bevacizumab combination therapy in clinical practice. When stratified for a validated prognostic index, the predictive model for response was significantly associated with improved overall survival.ConclusionTwo genes (low angiotensinogen and high HLA-class II expression) were predictive for bevacizumab response and were included in a predictive model for response. This model can be used in clinical practice to identify patients who will benefit from bevacizumab combination therapy.

KW - Predictive model

KW - Angiotensin

KW - Vascular normalization

KW - Immune activation

KW - Anti-angiogenic treatment

KW - Glioblastoma

KW - Antigen presentation

U2 - 10.1016/j.molonc.2016.05.005

DO - 10.1016/j.molonc.2016.05.005

M3 - Journal article

C2 - 27262894

VL - 10

SP - 1160

EP - 1168

JO - Molecular Oncology

JF - Molecular Oncology

SN - 1574-7891

IS - 8

ER -