MTR-18 Predictive Biomarkers Of Bevacizumab Response In Recurrent Glioblastoma Patients

Thomas Urup; Signe Regner Michaelsen; Lars Rønn Olsen; Anders Toft; Ib Jarle Christensen; Kirsten Grunnet; Helle Broholm; Michael Kosteljanetz; Hans Skovgaard Poulsen; Ulrik Lassen

doi:10.1093/neuonc/nov219.18

MTR-18 Predictive Biomarkers Of Bevacizumab Response In Recurrent Glioblastoma Patients

Thomas Urup, Signe Regner Michaelsen, Lars Rønn Olsen, Anders Toft, Ib Jarle Christensen, Kirsten Grunnet, Helle Broholm, Michael Kosteljanetz, Hans Skovgaard Poulsen, Ulrik Lassen

Research output: Contribution to journal › Conference abstract in journal › Research › peer-review

Abstract

Bevacizumab (BEV) plus chemotherapy has shown activity in recurrent glioblastoma (GBM). However, the prognosis varies and only one third of patients have a durable clinical response to BEV combination therapy. Recent findings from a randomized phase-3 study (AVAglio) indicate that patients with the proneural GBM subtype have a survival benefit when treated with BEV in combination with standard treatment. However, no validated biomarkers able to predict BEV response have been identified and the biology reflecting a clinical BEV response is poorly understood. The primary objective of this study was to evaluate the predictive and prognostic value of GBM subtypes in recurrent GBM patients treated with BEV therapy. The secondary objective was to identify biomarkers able to predict response to BEV therapy in recurrent GBM patients. METHODS: A total of 90 recurrent GBM patients treated with BEV combination treatment according to previously published protocols were included. Inclusion criteria: BEV plus irinotecan treatment in the period between May 2005-2011; available GBM tissue (according to WHO); response evaluable (RANO). RNA was extracted from laser microdissected tumor tissue and analyzed by the NanoString platform covering 800 genes. Raw data was assigned to molecular subtypes for each of the samples using the PAMR classifier model, previously trained on the AVAglio dataset. By performing a t-test, comparing gene profiles of patients responding versus progressing on BEV novel candidate biomarkers were identified. Candidate biomarkers were analyzed by logistic regression and Cox regression modelling response and survival endpoints, respectively. Biomarkers associated with response were added to a prognostic model consisting of three independent prognostic factors: Corticosteroid use, neurocognitive deficit and multifocal disease. RESULTS: Molecular subtypes were not associated with response or survival. However, two independent predictive biomarkers (gene1 down-regulated and gene2 up-regulated in responders, respectively) of BEV response and survival were identified. Results will be presented.

Original language	English
Journal	Neuro-Oncology
Volume	17
Issue number	suppl. 5
Pages (from-to)	v128-v128
Number of pages	1
ISSN	1522-8517
DOIs	https://doi.org/10.1093/neuonc/nov219.18
Publication status	Published - 2015
Event	The 20th Annual Scientific Meeting of the Society for Neuro-Oncology - San Antonio,Texas, United States Duration: 19 Nov 2015 → 22 Nov 2015 Conference number: 20 http://www.soc-neuro-onc.org/2015-annual-meeting/

Conference

Conference	The 20th Annual Scientific Meeting of the Society for Neuro-Oncology
Number	20
Country/Territory	United States
City	San Antonio,Texas
Period	19/11/2015 → 22/11/2015
Internet address	http://www.soc-neuro-onc.org/2015-annual-meeting/

Bibliographical note

Published by Oxford University Press on behalf of the Society for Neuro-Oncology 2015.

Access to Document

10.1093/neuonc/nov219.18

OpenUrl availability

Full text

Cite this

@article{77876c113cc74778806d9b62f7da8bef,

title = "MTR-18 Predictive Biomarkers Of Bevacizumab Response In Recurrent Glioblastoma Patients",

abstract = "Bevacizumab (BEV) plus chemotherapy has shown activity in recurrent glioblastoma (GBM). However, the prognosis varies and only one third of patients have a durable clinical response to BEV combination therapy. Recent findings from a randomized phase-3 study (AVAglio) indicate that patients with the proneural GBM subtype have a survival benefit when treated with BEV in combination with standard treatment. However, no validated biomarkers able to predict BEV response have been identified and the biology reflecting a clinical BEV response is poorly understood. The primary objective of this study was to evaluate the predictive and prognostic value of GBM subtypes in recurrent GBM patients treated with BEV therapy. The secondary objective was to identify biomarkers able to predict response to BEV therapy in recurrent GBM patients. METHODS: A total of 90 recurrent GBM patients treated with BEV combination treatment according to previously published protocols were included. Inclusion criteria: BEV plus irinotecan treatment in the period between May 2005-2011; available GBM tissue (according to WHO); response evaluable (RANO). RNA was extracted from laser microdissected tumor tissue and analyzed by the NanoString platform covering 800 genes. Raw data was assigned to molecular subtypes for each of the samples using the PAMR classifier model, previously trained on the AVAglio dataset. By performing a t-test, comparing gene profiles of patients responding versus progressing on BEV novel candidate biomarkers were identified. Candidate biomarkers were analyzed by logistic regression and Cox regression modelling response and survival endpoints, respectively. Biomarkers associated with response were added to a prognostic model consisting of three independent prognostic factors: Corticosteroid use, neurocognitive deficit and multifocal disease. RESULTS: Molecular subtypes were not associated with response or survival. However, two independent predictive biomarkers (gene1 down-regulated and gene2 up-regulated in responders, respectively) of BEV response and survival were identified. Results will be presented.",

author = "Thomas Urup and Michaelsen, {Signe Regner} and Olsen, {Lars R{\o}nn} and Anders Toft and Christensen, {Ib Jarle} and Kirsten Grunnet and Helle Broholm and Michael Kosteljanetz and Poulsen, {Hans Skovgaard} and Ulrik Lassen",

note = "Published by Oxford University Press on behalf of the Society for Neuro-Oncology 2015.; The 20th Annual Scientific Meeting of the Society for Neuro-Oncology ; Conference date: 19-11-2015 Through 22-11-2015",

year = "2015",

doi = "10.1093/neuonc/nov219.18",

language = "English",

volume = "17",

pages = "v128--v128",

journal = "Neuro-Oncology",

issn = "1522-8517",

publisher = "Oxford University Press",

number = "suppl. 5",

url = "http://www.soc-neuro-onc.org/2015-annual-meeting/",

}

TY - ABST

T1 - MTR-18 Predictive Biomarkers Of 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 - Broholm, Helle

AU - Kosteljanetz, Michael

AU - Poulsen, Hans Skovgaard

AU - Lassen, Ulrik

N1 - Conference code: 20

PY - 2015

Y1 - 2015

N2 - Bevacizumab (BEV) plus chemotherapy has shown activity in recurrent glioblastoma (GBM). However, the prognosis varies and only one third of patients have a durable clinical response to BEV combination therapy. Recent findings from a randomized phase-3 study (AVAglio) indicate that patients with the proneural GBM subtype have a survival benefit when treated with BEV in combination with standard treatment. However, no validated biomarkers able to predict BEV response have been identified and the biology reflecting a clinical BEV response is poorly understood. The primary objective of this study was to evaluate the predictive and prognostic value of GBM subtypes in recurrent GBM patients treated with BEV therapy. The secondary objective was to identify biomarkers able to predict response to BEV therapy in recurrent GBM patients. METHODS: A total of 90 recurrent GBM patients treated with BEV combination treatment according to previously published protocols were included. Inclusion criteria: BEV plus irinotecan treatment in the period between May 2005-2011; available GBM tissue (according to WHO); response evaluable (RANO). RNA was extracted from laser microdissected tumor tissue and analyzed by the NanoString platform covering 800 genes. Raw data was assigned to molecular subtypes for each of the samples using the PAMR classifier model, previously trained on the AVAglio dataset. By performing a t-test, comparing gene profiles of patients responding versus progressing on BEV novel candidate biomarkers were identified. Candidate biomarkers were analyzed by logistic regression and Cox regression modelling response and survival endpoints, respectively. Biomarkers associated with response were added to a prognostic model consisting of three independent prognostic factors: Corticosteroid use, neurocognitive deficit and multifocal disease. RESULTS: Molecular subtypes were not associated with response or survival. However, two independent predictive biomarkers (gene1 down-regulated and gene2 up-regulated in responders, respectively) of BEV response and survival were identified. Results will be presented.

AB - Bevacizumab (BEV) plus chemotherapy has shown activity in recurrent glioblastoma (GBM). However, the prognosis varies and only one third of patients have a durable clinical response to BEV combination therapy. Recent findings from a randomized phase-3 study (AVAglio) indicate that patients with the proneural GBM subtype have a survival benefit when treated with BEV in combination with standard treatment. However, no validated biomarkers able to predict BEV response have been identified and the biology reflecting a clinical BEV response is poorly understood. The primary objective of this study was to evaluate the predictive and prognostic value of GBM subtypes in recurrent GBM patients treated with BEV therapy. The secondary objective was to identify biomarkers able to predict response to BEV therapy in recurrent GBM patients. METHODS: A total of 90 recurrent GBM patients treated with BEV combination treatment according to previously published protocols were included. Inclusion criteria: BEV plus irinotecan treatment in the period between May 2005-2011; available GBM tissue (according to WHO); response evaluable (RANO). RNA was extracted from laser microdissected tumor tissue and analyzed by the NanoString platform covering 800 genes. Raw data was assigned to molecular subtypes for each of the samples using the PAMR classifier model, previously trained on the AVAglio dataset. By performing a t-test, comparing gene profiles of patients responding versus progressing on BEV novel candidate biomarkers were identified. Candidate biomarkers were analyzed by logistic regression and Cox regression modelling response and survival endpoints, respectively. Biomarkers associated with response were added to a prognostic model consisting of three independent prognostic factors: Corticosteroid use, neurocognitive deficit and multifocal disease. RESULTS: Molecular subtypes were not associated with response or survival. However, two independent predictive biomarkers (gene1 down-regulated and gene2 up-regulated in responders, respectively) of BEV response and survival were identified. Results will be presented.

U2 - 10.1093/neuonc/nov219.18

DO - 10.1093/neuonc/nov219.18

M3 - Conference abstract in journal

SN - 1522-8517

VL - 17

SP - v128-v128

JO - Neuro-Oncology

JF - Neuro-Oncology

IS - suppl. 5

T2 - The 20th Annual Scientific Meeting of the Society for Neuro-Oncology

Y2 - 19 November 2015 through 22 November 2015

ER -

MTR-18 Predictive Biomarkers Of Bevacizumab Response In Recurrent Glioblastoma Patients

Abstract

Conference

Bibliographical note

Access to Document

OpenUrl availability

Fingerprint

Cite this