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. 2024 Feb 16;24(1):222.
doi: 10.1186/s12885-024-11970-y.

Distinguishing IDH mutation status in gliomas using FTIR-ATR spectra of peripheral blood plasma indicating clear traces of protein amyloid aggregation

Saiko Kino  1 , Masayuki Kanamori  2 , Yoshiteru Shimoda  2 , Kuniyasu Niizuma  3   4 , Hidenori Endo  2 , Yuji Matsuura  5
Affiliations

Distinguishing IDH mutation status in gliomas using FTIR-ATR spectra of peripheral blood plasma indicating clear traces of protein amyloid aggregation

Saiko Kino et al. BMC Cancer. .

Abstract

Background: Glioma is a primary brain tumor and the assessment of its molecular profile in a minimally invasive manner is important in determining treatment strategies. Among the molecular abnormalities of gliomas, mutations in the isocitrate dehydrogenase (IDH) gene are strong predictors of treatment sensitivity and prognosis. In this study, we attempted to non-invasively diagnose glioma development and the presence of IDH mutations using multivariate analysis of the plasma mid-infrared absorption spectra for a comprehensive and sensitive view of changes in blood components associated with the disease and genetic mutations. These component changes are discussed in terms of absorption wavenumbers that contribute to differentiation.

Methods: Plasma samples were collected at our institutes from 84 patients with glioma (13 oligodendrogliomas, 17 IDH-mutant astrocytoma, 7 IDH wild-type diffuse glioma, and 47 glioblastomas) before treatment initiation and 72 healthy participants. FTIR-ATR spectra were obtained for each plasma sample, and PLS discriminant analysis was performed using the absorbance of each wavenumber in the fingerprint region of biomolecules as the explanatory variable. This data was used to distinguish patients with glioma from healthy participants and diagnose the presence of IDH mutations.

Results: The derived classification algorithm distinguished the patients with glioma from healthy participants with 83% accuracy (area under the curve (AUC) in receiver operating characteristic (ROC) = 0.908) and diagnosed the presence of IDH mutation with 75% accuracy (AUC = 0.752 in ROC) in cross-validation using 30% of the total test data. The characteristic changes in the absorption spectra suggest an increase in the ratio of β-sheet structures in the conformational composition of blood proteins of patients with glioma. Furthermore, these changes were more pronounced in patients with IDH-mutant gliomas.

Conclusions: The plasma infrared absorption spectra could be used to diagnose gliomas and the presence of IDH mutations in gliomas with a high degree of accuracy. The spectral shape of the protein absorption band showed that the ratio of β-sheet structures in blood proteins was significantly higher in patients with glioma than in healthy participants, and protein aggregation was a distinct feature in patients with glioma with IDH mutations.

Keywords: Amyloid; Blood biomarkers; Glioma; IDH mutation; Mid-infrared absorption spectroscopy; Protein aggregation.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
Fourier transform infrared-attenuated total reflection (FTIR-ATR) measurement system
Fig. 2
Fig. 2
Temporal variation of infrared ATR spectra of plasma with drying. Each absorption spectrum is different in the time elapsed to start the ATR spectrum measurement after the plasma sample is applied to the top surface of the prism (blue: 0 min, orange: 6 min, gray: 12 min, green: 20 min, light blue: 30 min, yellow: 40 min). The overall absorbance increases as the sample dries (in the direction of the gray arrow); the sample dries completed in approximately 20 min and the absorbance stabilizes thereafte
Fig. 3
Fig. 3
Mean values for each group in the second derivative spectrum of plasma. Glioma group (84 patients) and healthy group (72 persons)
Fig. 4
Fig. 4
Discriminant score distribution and receiver operating characteristic (ROC) curves. For PLS discrimination of glioma and control groups from plasma infrared absorption spectra with 2 components. Cross-validation of LOO and 30% of the test data
Fig. 5
Fig. 5
Variable importance of projection in PLS discrimination of glioma from plasma infrared absorption spectra
Fig. 6
Fig. 6
Mean values for each group in the second derivative spectrum of plasma. Isocitrate dehydrogenase (IDH)-mutant (30 patients) and IDH wild-type (54 patients) groups
Fig. 7
Fig. 7
Discriminant score distribution and ROC curves. For PLS discrimination of IDH-mutant and wild-type groups from plasma infrared absorption spectra with 1 component. Cross-validation of LOO and 30% of the test data
Fig. 8
Fig. 8
Variable importance of projection in PLS discrimination of IDH mutations from plasma infrared absorption spectra
Fig. 9
Fig. 9
FTIR-ATR spectra of 2-hydroxyglutarate (2-HG) and differences in spectra associated with IDH mutation. The upper panel shows the FTIR-ATR spectrum of 2-HG corresponding to 0.5 wt% (26 mM), and the lower panel shows its second derivative spectrum (blue line) and the difference between the average second derivative spectra of the IDH-mutant and IDH wild-type samples in Fig. 6 (red line)
Fig. 10
Fig. 10
Mean values for each group in the second derivative spectrum of plasma. IDH-mutant glioma group (30 patients), IDH wild-type glioma group (54 patients), and healthy control group (72 persons)
Fig. 11
Fig. 11
Age distribution of 30 patients with IDH-mutant glioma and 54 patients with IDH wild-type glioma
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