Multigene profiling to identify alternative treatment options for glioblastoma: a pilot study. Issue 7 (2nd April 2014)

• Record Type: Journal Article
• Authors: Tabone, Tania; Abuhusain, Hazem J; Nowak, Anna K; Erber, Wendy N; McDonald, Kerrie L
• Is Part Of: Journal of clinical pathology. Volume 67:Issue 7(2014)
• Page Start: 550
• Page End: 555
• Publication Date: 2014-04-02
• Subjects: Pathology -- Periodicals; Pathology, Molecular -- Periodicals; 616.0705
• DOI: 10.1136/jclinpath-2014-202173
• Languages: English
• ISSNs: 0021-9746

Abstract

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.