Rapid Spectroscopic Liquid Biopsy for the Universal Detection of Brain Tumours.

chemometrics clinical translation early detection glioma vibrational spectroscopy

Journal

Cancers
ISSN: 2072-6694
Titre abrégé: Cancers (Basel)
Pays: Switzerland
ID NLM: 101526829

Informations de publication

Date de publication:
30 Jul 2021
Historique:
received: 24 06 2021
revised: 22 07 2021
accepted: 29 07 2021
entrez: 7 8 2021
pubmed: 8 8 2021
medline: 8 8 2021
Statut: epublish

Résumé

To support the early detection and diagnosis of brain tumours we have developed a rapid, cost-effective and easy to use spectroscopic liquid biopsy based on the absorbance of infrared radiation. We have previously reported highly sensitive results of our approach which can discriminate patients with a recent brain tumour diagnosis and asymptomatic controls. Other liquid biopsy approaches (e.g., based on tumour genetic material) report a lower classification accuracy for early-stage tumours. In this manuscript we present an investigation into the link between brain tumour volume and liquid biopsy test performance. In a cohort of 177 patients (90 patients with high-grade glioma (glioblastoma (GBM) or anaplastic astrocytoma), or low-grade glioma (astrocytoma, oligoastrocytoma and oligodendroglioma)) tumour volumes were calculated from magnetic resonance imaging (MRI) investigations and patients were split into two groups depending on MRI parameters (T1 with contrast enhancement or T2/FLAIR (fluid-attenuated inversion recovery)). Using attenuated total reflection (ATR)-Fourier transform infrared (FTIR) spectroscopy coupled with supervised learning methods and machine learning algorithms, 90 tumour patients were stratified against 87 control patients who displayed no symptomatic indications of cancer, and were classified as either glioma or non-glioma. Sensitivities, specificities and balanced accuracies were all greater than 88%, the area under the curve (AUC) was 0.98, and cancer patients with tumour volumes as small as 0.2 cm Our spectroscopic liquid biopsy approach can identify gliomas that are both small and low-grade showing great promise for deployment of this technique for early detection and diagnosis.

Sections du résumé

BACKGROUND BACKGROUND
To support the early detection and diagnosis of brain tumours we have developed a rapid, cost-effective and easy to use spectroscopic liquid biopsy based on the absorbance of infrared radiation. We have previously reported highly sensitive results of our approach which can discriminate patients with a recent brain tumour diagnosis and asymptomatic controls. Other liquid biopsy approaches (e.g., based on tumour genetic material) report a lower classification accuracy for early-stage tumours. In this manuscript we present an investigation into the link between brain tumour volume and liquid biopsy test performance.
METHODS METHODS
In a cohort of 177 patients (90 patients with high-grade glioma (glioblastoma (GBM) or anaplastic astrocytoma), or low-grade glioma (astrocytoma, oligoastrocytoma and oligodendroglioma)) tumour volumes were calculated from magnetic resonance imaging (MRI) investigations and patients were split into two groups depending on MRI parameters (T1 with contrast enhancement or T2/FLAIR (fluid-attenuated inversion recovery)). Using attenuated total reflection (ATR)-Fourier transform infrared (FTIR) spectroscopy coupled with supervised learning methods and machine learning algorithms, 90 tumour patients were stratified against 87 control patients who displayed no symptomatic indications of cancer, and were classified as either glioma or non-glioma.
RESULTS RESULTS
Sensitivities, specificities and balanced accuracies were all greater than 88%, the area under the curve (AUC) was 0.98, and cancer patients with tumour volumes as small as 0.2 cm
CONCLUSIONS CONCLUSIONS
Our spectroscopic liquid biopsy approach can identify gliomas that are both small and low-grade showing great promise for deployment of this technique for early detection and diagnosis.

Identifiants

pubmed: 34359751
pii: cancers13153851
doi: 10.3390/cancers13153851
pmc: PMC8345395
pii:
doi:

Types de publication

Journal Article

Langues

eng

Subventions

Organisme : Cancer Research UK
ID : A28345
Pays : United Kingdom

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Auteurs

Ashton G Theakstone (AG)

Technology and Innovation Centre, Department of Pure and Applied Chemistry, University of Strathclyde, Glasgow G1 1RD, UK.

Paul M Brennan (PM)

Translational Neurosurgery, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh EH16 4SB, UK.

Michael D Jenkinson (MD)

The Walton Centre NHS Foundation Trust, Lower Lane, Liverpool L9 7LJ, UK.
Department of Pharmacology & Therapeutics, Institute of System, Molecular and Integrative Biology, University of Liverpool, Liverpool L69 7ZB, UK.

Samantha J Mills (SJ)

The Walton Centre NHS Foundation Trust, Lower Lane, Liverpool L9 7LJ, UK.

Khaja Syed (K)

The Walton Centre NHS Foundation Trust, Lower Lane, Liverpool L9 7LJ, UK.

Christopher Rinaldi (C)

Technology and Innovation Centre, Department of Pure and Applied Chemistry, University of Strathclyde, Glasgow G1 1RD, UK.

Yun Xu (Y)

Department of Biochemistry and Systems Biology, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool L69 7ZB, UK.

Royston Goodacre (R)

Department of Biochemistry and Systems Biology, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool L69 7ZB, UK.

Holly J Butler (HJ)

Dxcover Limited, 204 George Street, Glasgow G1 1XW, UK.

David S Palmer (DS)

Dxcover Limited, 204 George Street, Glasgow G1 1XW, UK.
Department of Pure and Applied Chemistry, University of Strathclyde, Thomas Graham Building, Glasgow G1 1XL, UK.

Benjamin R Smith (BR)

Dxcover Limited, 204 George Street, Glasgow G1 1XW, UK.

Matthew J Baker (MJ)

Dxcover Limited, 204 George Street, Glasgow G1 1XW, UK.

Classifications MeSH