Related Experiment Video
Updated: Sep 29, 2025
Evaluation of Biomarkers in Glioma by Immunohistochemistry on Paraffin-Embedded 3D Glioma Neurosphere Cultures
Published on: January 9, 2019
Utilisation of semiconductor sequencing for the detection of predictive biomarkers in glioblastoma
Gareth Williams1, Alexander Llewelyn1, Robert Thatcher1
1Oncologica UK Ltd, Cambridge, United Kingdom.
Abstract:
The standard treatment for glioblastoma involves a combination of surgery, radiation and chemotherapy but have limited impact on survival. The exponential increase in targeted agents directed at pivotal oncogenic pathways now provide new therapeutic opportunities for this tumour type. However, lack of comprehensive precision oncology testing at diagnosis means such therapeutic opportunities are potentially overlooked. To investigate the role of semiconductor sequencing for detection of predictive biomarkers in routine glioblastoma samples we have undertaken analysis of test trending data generated by a clinically validated next generation sequencing platform designed to capture actionable genomic variants distributed across 505 genes. Analysis was performed across a cohort of 55 glioblastoma patients. Analysis of trending data has revealed a complex and rich actionable mutational landscape in which 166 actionable mutations were detected across 36 genes linked to 17 off label targeted therapy protocols and 111 clinical trials. The majority of patients harboured three or more actionable mutations affecting key cancer related regulatory networks including the PI3K/AKT/MTOR and RAS/RAF/MEK/MAPK signalling pathways, DNA-damage repair pathways and cell cycle checkpoints. Linkage with immunotherapy and PARP inhibitors was identified in 44% of glioblastoma patients as a consequence of alterations in DNA-damage repair genes. Taken together our data indicates that precision oncology testing utilising semiconductor sequencing can be used to identify a broad therapeutic armamentarium of targeted therapies and immunotherapies that can be potentially employed for the improved clinical management of glioblastoma patients.
Insights
Precision oncology testing using semiconductor sequencing reveals numerous actionable mutations in glioblastoma. This identifies potential targeted therapies and immunotherapies to improve patient outcomes.
Area of Science:
- Oncology
- Genomics
- Molecular Biology
Background:
- Standard glioblastoma treatment (surgery, radiation, chemotherapy) offers limited survival benefits.
- Targeted agents offer new therapeutic avenues, but are often overlooked due to inadequate precision oncology testing.
- Identifying predictive biomarkers is crucial for effective glioblastoma treatment.
Purpose of the Study:
- To evaluate semiconductor sequencing for detecting predictive biomarkers in glioblastoma.
- To analyze actionable genomic variants in a glioblastoma patient cohort.
- To explore therapeutic opportunities based on identified mutations.
Main Methods:
- Analysis of test trending data from a clinically validated next-generation sequencing platform.
- Utilized a platform covering 505 genes for variant detection.
- Examined data from 55 glioblastoma patients.
Main Results:
- Detected 166 actionable mutations across 36 genes in the patient cohort.
- Identified links to 17 off-label targeted therapy protocols and 111 clinical trials.
- Found that most patients had ≥3 actionable mutations in key cancer pathways (PI3K/AKT/MTOR, RAS/RAF/MEK/MAPK, DNA-damage repair, cell cycle).
- Observed a 44% linkage to immunotherapy and PARP inhibitors due to DNA-damage repair gene alterations.
Conclusions:
- Semiconductor sequencing effectively identifies a wide range of actionable mutations in glioblastoma.
- Precision oncology testing can guide the selection of targeted therapies and immunotherapies.
- This approach holds potential for improved clinical management of glioblastoma.
