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Multigene profiling to identify alternative treatment options for glioblastoma: a pilot study
  1. Tania Tabone1,
  2. Hazem J Abuhusain2,
  3. Anna K Nowak3,
  4. Australian Genomics and Clinical Outcome of Glioma (AGOG) Network,
  5. Wendy N Erber1,
  6. Kerrie L McDonald2
  1. 1Translational Cancer Pathology Laboratory, School of Pathology and Laboratory Medicine, University of Western Australia, Crawley, Western Australia, Australia
  2. 2Cure Brain Cancer Neuro-oncology Group, Prince of Wales Clinical School, UNSW Australia
  3. 3Department of Medical Oncology, School of Medicine and Pharmacology, University of Western Australia, Sir Charles Gairdner Hospital, Nedlands, Western Australia, Australia
  1. Correspondence to Dr Kerrie L McDonald, Cure Brain Cancer Neuro-oncology Group, Prince of Wales Clinical School, Level 2, Lowy Cancer Research Centre, UNSW, Kensington, New South Wales 2052, Australia; k.mcdonald{at}unsw.edu.au

Abstract

Glioblastoma (GBM) is a highly aggressive malignancy and the most effective treatment regime has a high relapse rate. Increasingly, the development of therapies involves defining drug–diagnostic combinations where the presence of a molecular target or marker identifies patients who are most likely to respond to a specific therapy. Trials in other solid cancers have demonstrated clear utility in the incorporation of biomarkers to stratify patients to targeted treatment, however, there are no mutations that are currently used to inform treatment options for GBM.

Aims We piloted the use of high-throughput next-generation sequencing technology to identify genetic mutations in 44 GBM specimens that may be amenable to current or future targeted therapeutic strategies.

Method Somatic mutation profiling was performed using the AmpliSeq Cancer Hotspot Panel v2 and semiconductor sequencing technology.

Results A total of 66 mutations were detected in 35/44 (80%) patients. The number of mutations per tumour ranged from 0 to 4 (average per tumour=1.5). The most frequent mutations were in TP53 (n=12), PTEN (n=9), EGFR (n=8) and PIK3CA (n=5). Clinically actionable somatic mutations were detected in 24/35 (69%) patients.

Conclusions This study demonstrates that the use of an ‘off-the-shelf’ oncogene primer panel and benchtop next-generation sequencer can identify mutations and potentially actionable targets in the majority of GBM patients. Data from this pilot highlights the potential for targeted genetic resequencing to identify mutations that may inform treatment options and predict outcomes.

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