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. 2021 Jul 7;6(4):902-916.
doi: 10.1093/jalm/jfaa233.

Intraoperative Mass Spectrometry Platform for IDH Mutation Status Prediction, Glioma Diagnosis, and Estimation of Tumor Cell Infiltration

Affiliations

Intraoperative Mass Spectrometry Platform for IDH Mutation Status Prediction, Glioma Diagnosis, and Estimation of Tumor Cell Infiltration

Hannah Marie Brown et al. J Appl Lab Med. .

Abstract

Background: Surgical tumor resection is the primary treatment option for diffuse glioma, the most common malignant brain cancer. The intraoperative diagnosis of gliomas from tumor core samples can be improved by use of molecular diagnostics. Further, residual tumor at surgical margins is a primary cause of tumor recurrence and malignant progression. This study evaluates a desorption electrospray ionization mass spectrometry (DESI-MS) system for intraoperative isocitrate dehydrogenase (IDH) mutation assessment, estimation of tumor cell infiltration as tumor cell percentage (TCP), and disease status. This information could be used to enhance the extent of safe resection and so potentially improve patient outcomes.

Methods: A mobile DESI-MS instrument was modified and used in neurosurgical operating rooms (ORs) on a cohort of 49 human subjects undergoing craniotomy with tumor resection for suspected diffuse glioma. Small tissue biopsies (ntotal = 203) from the tumor core and surgical margins were analyzed by DESI-MS in the OR and classified using univariate and multivariate statistical methods.

Results: Assessment of IDH mutation status using DESI-MS/MS to measure 2-hydroxyglutarate (2-HG) ion intensities from tumor cores yielded a sensitivity, specificity, and overall diagnostic accuracy of 89, 100, and 94%, respectively (ncore = 71). Assessment of TCP (categorized as low or high) in tumor margin and core biopsies using N-acetyl-aspartic acid (NAA) intensity provided a sensitivity, specificity, and accuracy of 91, 76, and 83%, respectively (ntotal = 203). TCP assessment using lipid profile deconvolution provided sensitivity, specificity, and accuracy of 76, 85, and 81%, respectively (ntotal = 203). Combining the experimental data and using PCA-LDA predictions of disease status, the sensitivity, specificity, and accuracy in predicting disease status are 63%, 83%, and 74%, respectively (ntotal = 203).

Conclusions: The DESI-MS system allowed for identification of IDH mutation status, glioma diagnosis, and estimation of tumor cell infiltration intraoperatively in a large human glioma cohort. This methodology should be further refined for clinical diagnostic applications.

Keywords: ambient ionization mass spectrometry; diffuse glioma; isocitrate dehydrogenase mutation; molecular cancer diagnostics; molecular pathology; point-of-care diagnostics.

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Conflict of interest statement

Authors’ Disclosures or Potential Conflicts of Interest: Upon manuscript submission, all authors completed the author disclosure form. Disclosures and/or potential conflicts of interest. Employment or Leadership: None declared. Consultant or Advisory Role: None declared. Stock Ownership: None declared. Honoraria: None declared. Research Funding: This research was supported by the National Institute of Biomedical Imaging and Bioengineering (NIH grant no. R21EB015722). Support of the Purdue Center for Cancer Research, NIH grant P30 CA023168, is gratefully acknowledged. This publication was made possible with partial support for Clint Alfaro from grant no. UL1TR001108 (to A. Shekhar, principal investigator) from the National Institutes of Health, National Center for Advancing Translational Sciences, Clinical and Translational Sciences Award. Expert Testimony: None declared. Patents: R.G. Cooks, 7,335,897.

Figures

Fig. 1.
Fig. 1.
Summary of the DESI-MS method. (A) Smeared tissue (pink) is analyzed with DESI spray using a zigzag raster pattern (dotted lines, with direction noted by arrow heads), spanning 12 mm in x-dimension and 25 mm in y-dimension over 1.1 min; the pattern is repeated 3 times. The DESI spot is offset 0.5 mm in the y-dimension after each raster loop. (B) DESI spray position and the timeline for the DESI-MS method. The (x, y) coordinates denote the starting position of the DESI spot for each raster loop. (C) Description of the 2 DESI-MS methods, shown synchronized with the position of the moving stage. A different set of MS data is collected during each method segment. Note the use of full MS, MS/MS (MS2), and MS3 experiments. (D) Summary of number of patients, biopsies, and smears, noting how many were excluded, and which subjects are new to the study. See Supplemental Tables 2–5 for additional patient cohort data. Data from earlier subjects recruited in the study were published in Reference for glioma diagnosis and TCP, and in Reference for IDH-mutation assessment. DESI data was considered an outlier if no lipid or metabolite profile scans were retained after data filtering due to low signal or high similarity to data collected from a blank glass slide (see Supplemental Methods for data filtering methods).
Fig. 2.
Fig. 2.
Intraoperative assessment of IDH-mutation status from tumor cores. (A) Chemical structure of α-ketoglutaric acid and 2-hydroxyglutarate (2-HG), the oncometabolite associated with IDH mutations. (B) ROC curve for the IDH-mutation assay using the tumor core biopsies. The area under the curve is 0.98, indicating the high accuracy of the method. (C) Box-plot showing the average summed and TIC normalized MS3 fragment ion intensities (m/z 85 + m/z 101) produced by sequential dissociation (MS3) of 2-HG for all tumor core biopsies (n = 68 biopsies from 28 subjects) by IDH mutation status. The fragment ion intensities from duplicate smears of the same biopsy were averaged to generate one value per biopsy. Error bars represent ± 1.5 times the calculated standard deviations. The black dashed horizontal decision line was calculated from ROC curve analysis and differentiates tumor core biopsies from IDH-mut subjects and IDH-wt subjects with the highest sensitivity and specificity.
Fig. 3.
Fig. 3.
DESI-MS predictions of disease status, TCP, and IDH-mutation status for a core and margin biopsy from Subject 58. (A) Reconstruction of MRI tumor volume showing location of the two biopsies. Biopsy 328 (red dot) is within the contrast enhancing region of the tumor; biopsy 333 (blue dot) is a few mm outside of the contrast enhancing region. (B–D) The lipid, metabolite, and MS3 product ion scans for biopsy 328 (red dot in Fig. 2, A). (E–G) The lipid, metabolite, and 2-HG MS3 product ion scan for biopsy 333 (blue dot in Fig. 2, A). Biopsy 328 was classified as glioma, high TCP, and IDH-mut; biopsy 333 was infiltrative margin (white matter), low TCP, and IDH-mut.

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