Rapid spectroscopic liquid biopsy for the universal detection of brain tumours

Ashton G. Theakstone, Paul M. Brennan, Michael D. Jenkinson, Samantha J. Mills, Khaja Syed, Christopher Rinaldi, Yun Xu, Royston Goodacre, Holly J. Butler, David S. Palmer, Benjamin R. Smith, Matthew J. Baker

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Abstract

Background: To support the early detection and diagnosis of brain tumours we have developed a rapid, cost-effective 26 and easy to use spectroscopic liquid biopsy based on the absorbance of infrared radiation. We have previously reported highly 27 sensitive results of our approach which can discriminate patients with a recent brain tumour diagnosis and asymptomatic controls. 28 Other liquid biopsy approaches (e.g., based on tumour genetic material) report a lower classification accuracy for early-stage 29 tumours. In this manuscript we present an investigation into the link between brain tumour volume and liquid biopsy test 30 performance. Methods: In a cohort of 177 patients (90 patients with high-grade glioma (glioblastoma (GBM) or anaplastic 31 astrocytoma), or low-grade glioma (astrocytoma, oligoastrocytoma and oligodendroglioma)) tumour volumes were calculated from 32 magnetic resonance imaging (MRI) investigations and patients were split into two groups depending on MRI parameters (T1 with 33 contrast enhancement or T2/FLAIR). Using ATR-FTIR spectroscopy coupled with supervised learning methods and machine learning 34 algorithms, 90 tumour patients were stratified against 87 control patients who displayed no symptomatic indications of cancer, and 35 were classified as either glioma or non-glioma. Results: Sensitivities, specificities and balanced accuracies were all greater than 88%, 36 the area under the curve (AUC) was 0.98, and cancer patients with tumour volumes as small as 0.2 cm3 were correctly identified. 37 Conclusions: Our spectroscopic liquid biopsy approach can identify gliomas that are both small and low-grade showing great 38 promise for deployment of this technique for early detection and diagnosis.
Original languageEnglish
Article number3851
Number of pages13
JournalCancers
Volume13
Issue number15
DOIs
Publication statusPublished - 30 Jul 2021

Keywords

  • vibrational spectroscopy
  • glioma
  • chemometrics
  • clinical translation
  • early detection

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