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. 2014 Oct 21;111(42):15184-9.
doi: 10.1073/pnas.1408129111. Epub 2014 Sep 22.

Application of desorption electrospray ionization mass spectrometry imaging in breast cancer margin analysis

Affiliations

Application of desorption electrospray ionization mass spectrometry imaging in breast cancer margin analysis

David Calligaris et al. Proc Natl Acad Sci U S A. .

Abstract

Distinguishing tumor from normal glandular breast tissue is an important step in breast-conserving surgery. Because this distinction can be challenging in the operative setting, up to 40% of patients require an additional operation when traditional approaches are used. Here, we present a proof-of-concept study to determine the feasibility of using desorption electrospray ionization mass spectrometry imaging (DESI-MSI) for identifying and differentiating tumor from normal breast tissue. We show that tumor margins can be identified using the spatial distributions and varying intensities of different lipids. Several fatty acids, including oleic acid, were more abundant in the cancerous tissue than in normal tissues. The cancer margins delineated by the molecular images from DESI-MSI were consistent with those margins obtained from histological staining. Our findings prove the feasibility of classifying cancerous and normal breast tissues using ambient ionization MSI. The results suggest that an MS-based method could be developed for the rapid intraoperative detection of residual cancer tissue during breast-conserving surgery.

Keywords: FT-ICR MS; intrasurgical diagnosis; metabolites; molecular pathology.

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Conflict of interest statement

Conflict of interest statement: In compliance with Harvard Medical School and Partners Healthcare guidelines on potential conflict of interest, we disclose that S.S. and N.Y.R.A. are scientific advisors to BayesianDx.

Figures

Fig. 1.
Fig. 1.
Profiled mass spectra in negative ion mode using DESI-MSI located 5 cm away from tumor (A) and 2 cm away from tumor (B) tissue sections from research subjects 14 and 9, respectively, and a tumor center tissue section from research subject 14 (C). (Right) Histological images of representative tissue regions are shown. (Magnification, 40×.) The red-dashed outlines display background peaks.
Fig. 2.
Fig. 2.
Average of 14 normalized mass spectra from DESI-MSI analysis of tumor tissue (A) and average of 14 normalized mass spectra from DESI-MSI analysis of normal tissue (B). (C) Subtraction between the two first mass spectra (i.e., AB).
Fig. 3.
Fig. 3.
DESI MS images from the tumor center (A), the tumor edge (B), 2 cm away from the tumor (C), 5 cm away from the tumor (D), and contralateral side (E) tissue sections from research subject 9 showing the distributions of ions at m/z 281.2, m/z 391.4, m/z 655.6, and m/z 885.7. (Right) Light microscopy images of the H&E-stained sections are shown. (Scale bars, 2 mm.)
Fig. 4.
Fig. 4.
DESI MS images from the tumor center (A), tumor edge (B), 2 cm away from the tumor (C), and 5 cm away from the tumor (D) tissue sections from research subject 14 showing the distributions of ions at m/z 281.2, m/z 391.4, m/z 655.6, and m/z 885.7. (Right) Light microscopy images of the H&E-stained sections are shown. (Scale bars, 2 mm.)
Fig. 5.
Fig. 5.
PCA analysis of DESI-MSI data from mastectomy research subjects 9 (A) and 14 (B). For research subject 9, score plots of the three first principal components (PC1–PC3) display mass spectra from the tumor center group (red dots), tumor edge group (green dots), group located 2 cm away from the tumor (blue dots), group located 5 cm away from the tumor (yellow dots), and contralateral side group (purple dots). For research subject 14, score plots of the three first principal components (PC1–PC3) display mass spectra from the tumor center group (red dots), tumor edge group (green dots), group located 2 cm away from the tumor (blue dots), and group located 5 cm away from tumor (yellow dots).

References

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