INTRODUCTION: The protein biomarkers alpha-fetoprotein and human chorionic gonadotropin currently used to diagnose malignant germ cell tumours (MGCTs) have limited sensitivity/specificity. ‘Marker-negative’ CNS-MGCT cases require biopsy, which carries substantial morbidity/mortality risks. Improved, minimally-invasive tests are therefore required to a) segregate CNS-MGCTs from other CNS lesions and b) discriminate between the marker-negative CNS-MGCT subtypes embryonal carcinoma and germinoma. We are currently developing microRNA-based tests to achieve the above aims, having previously identified a panel of four microRNAs (miR-371a-3p/miR-372-3p/miR-373-3p/miR-367-3p; miR-371 ∼ 3/367) that are elevated in extracranial-MGCT patient serum at diagnosis, which segregates extracranial-MGCTs from extracranial benign-GCTs/other malignancies. METHODS: Using qRT-PCR, we quantified miR-371 ∼ 3/367 levels at diagnosis in CSF and available matched-serum from patients with (suprasellar/pineal) CNS-MGCTs (n = 5) versus other CNS lesions (n = 3; low-grade-glioma, LCH, intracranial-relapsed neuroblastoma), plus serum from 7 other CNS lesions [low-grade-glioma (n = 6), medulloblastoma (n = 1)], and 8 non-malignant-controls. RESULTS: CSF miR-371 ∼ 3/367 levels were elevated in all five patients with CNS-MGCTs, compared with other CNS lesions. For the three CNS-MGCT patients where matching serum was available, serum levels of miR-371 ∼ 3/367 were also elevated when compared with serum levels in other CNS lesions and non-malignant-controls. CONCLUSIONS: Serum and CSF levels of miR-371 ∼ 3/367 reliably detect CNS-MGCTs at diagnosis. At present we are identifying serum/CSF microRNAs that differentiate between marker-negative embryonal carcinoma and germinoma subtypes of CNS-MGCTs. Our overall approach will ultimately assist both non-invasive CNS-MGCT diagnosis and risk-stratification, and thus inform subsequent treatment-planning.
. 2016 May 30;18(Suppl 3):iii44. doi: 10.1093/neuonc/now072.10
GC-10: A PROPOSED PATHWAY TOWARDS NON-INVASIVE microRNA-BASED DIAGNOSIS AND RISK STRATIFICATION OF CNS MALIGNANT GERM CELL TUMOURS
Emma Bell
1,2, Hannah Watson
1, Shivani Bailey
1, Isabella Syring
3, Jorg Ellinger
3, James Nicholson
4, Helen Brown
2, Benoit Destenaves
2, Nicholas Coleman
1,5, Matthew Murray
1,4
Emma Bell
1Department of Pathology, University of Cambridge, Cambridge, UK
2Personalised Healthcare and Biomarkers, AstraZeneca, Cambridge, UK
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Hannah Watson
1Department of Pathology, University of Cambridge, Cambridge, UK
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Shivani Bailey
1Department of Pathology, University of Cambridge, Cambridge, UK
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Isabella Syring
3Department of Urology, University Hospital Bonn, Bonn, Germany
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Jorg Ellinger
3Department of Urology, University Hospital Bonn, Bonn, Germany
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James Nicholson
4Department of Paediatric Haematology and Oncology, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
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Helen Brown
2Personalised Healthcare and Biomarkers, AstraZeneca, Cambridge, UK
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Benoit Destenaves
2Personalised Healthcare and Biomarkers, AstraZeneca, Cambridge, UK
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Nicholas Coleman
1Department of Pathology, University of Cambridge, Cambridge, UK
5Department of Histopathology, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
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Matthew Murray
1Department of Pathology, University of Cambridge, Cambridge, UK
4Department of Paediatric Haematology and Oncology, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
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1Department of Pathology, University of Cambridge, Cambridge, UK
2Personalised Healthcare and Biomarkers, AstraZeneca, Cambridge, UK
3Department of Urology, University Hospital Bonn, Bonn, Germany
4Department of Paediatric Haematology and Oncology, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
5Department of Histopathology, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
Issue date 2016 Jun.
© the author(s) 2016. published by oxford university press on behalf of the society for neuro-oncology. all rights reserved. for permissions, please e-mail: journals.permissions@oup.com
PMCID: PMC4903340
