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. 2022 Sep 12;23(18):10562.
doi: 10.3390/ijms231810562.

Rapid Evaporative Ionization Mass Spectrometry-Based Lipidomics for Identification of Canine Mammary Pathology

Domenica Mangraviti  1 , Jessica Maria Abbate  2 , Carmelo Iaria  1 , Francesca Rigano  1 , Luigi Mondello  1   3   4 , Marco Quartuccio  2 , Fabio Marino  1
Affiliations

Rapid Evaporative Ionization Mass Spectrometry-Based Lipidomics for Identification of Canine Mammary Pathology

Domenica Mangraviti et al. Int J Mol Sci. .

Abstract

The present work proposes the use of a fast analytical platform for the mass spectrometric (MS) profiling of canine mammary tissues in their native form for the building of a predictive statistical model. The latter could be used as a novel diagnostic tool for the real-time identification of different cellular alterations in order to improve tissue resection during veterinary surgery, as previously validated in human oncology. Specifically, Rapid Evaporative Ionization Mass Spectrometry (REIMS) coupled with surgical electrocautery (intelligent knife-iKnife) was used to collect MS data from histologically processed mammary samples, classified into healthy, hyperplastic/dysplastic, mastitis and tumors. Differences in the lipid composition enabled tissue discrimination with an accuracy greater than 90%. The recognition capability of REIMS was tested on unknown mammary samples, and all of them were correctly identified with a correctness score of 98-100%. Triglyceride identification was increased in healthy mammary tissues, while the abundance of phospholipids was observed in altered tissues, reflecting morpho-functional changes in cell membranes, and oxidized species were also tentatively identified as discriminant features. The obtained lipidomic profiles represented unique fingerprints of the samples, suggesting that the iKnife technique is capable of differentiating mammary tissues following chemical changes in cellular metabolism.

Keywords: CMT; REIMS; Rapid Evaporative Ionization Mass Spectrometry; canine mammary pathology; canine mammary tumors; iKnife; lipidomic; veterinary surgery.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
PCA score plot of healthy and pathological status included in the model.
Figure 2
Figure 2
Tridimensional visualization of PCA/LDA statistical model (A); bidimensional score lots along first three main linear discriminants (LD): LD1/LD2 (B) and LD1/LD3 (C).
Figure 3
Figure 3
Real-time identification of (A) healthy mammary gland, (B) comedocarcinoma as malignant tumor, (C) margin tissue of comedocarcinoma, (D) ductal ectasia.
Figure 4
Figure 4
Representative REIMS(-) spectra of (A) healthy mammary gland, (B) hyperplastic/dysplastic tissue, (C) mastitis, (D) tumor.
Figure 5
Figure 5
Loading plot relative to the PC1 component, explaining the 30.02% of the total variance of the model.
Figure 6
Figure 6
Loading plot relative to the PC2 component, explaining the 30.02% of the total variance of the model.
See this image and copyright information in PMC

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