Identification of transcriptome signature for predicting clinical response to bevacizumab in recurrent glioblastoma

Seung Won Choi, Hyemi Shin, Jason K. Sa, Hee Jin Cho, Harim Koo, Doo Sik Kong, Ho Jun Seol, Do Hyun Nam

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

Glioblastomas are among the most fatal brain tumors. Although no effective treatment option is available for recurrent glioblastomas (GBMs), a subset of patients evidently derived clinical benefit from bevacizumab, a monoclonal antibody against vascular endothelial growth factor. We retrospectively reviewed patients with recurrent GBM who received bevacizumab to identify biomarkers for predicting clinical response to bevacizumab. Following defined criteria, the patients were categorized into two clinical response groups, and their genetic and transcriptomic results were compared. Angiogenesis-related gene sets were upregulated in both responders and nonresponders, whereas genes for each corresponding angiogenesis pathway were distinct from one another. Two gene sets were made, namely, the nonresponder angiogenesis gene set (NAG) and responder angiogenesis gene set (RAG), and then implemented in independent GBM cohort to validate our dataset. A similar association between the corresponding gene set and survival was observed. In NAG, COL4A2 was associated with a poor clinical outcome in bevacizumab-treated patients. This study demonstrates that angiogenesis-associated gene sets are composed of distinct subsets with diverse biological roles and they represent different clinical responses to anti-angiogenic therapy. Enrichment of a distinct angiogenesis pathway may serve as a biomarker to predict patients who will derive a clinical benefit from bevacizumab.

Original languageEnglish
Pages (from-to)1774-1783
Number of pages10
JournalCancer Medicine
Volume7
Issue number5
DOIs
StatePublished - May 2018

Keywords

  • Angiogenesis
  • bevacizumab
  • biomarkers
  • gene expression signatures
  • glioblastoma

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