MSACL 2017 US Abstract

Simulated Breast Cancer Resection Margin Assessment using Desorption Electrospray Ionization (DESI) Mass Spectrometry Imaging (MSI) with Histology Correlation

Nicole Morse (Presenter)
Queen's University

Bio: Nicole Morse is a Pathology and Molecular Medicine Graduate Student at Queen's University who has developed an interest in clinical applications of mass spectrometry over two projects. Her current project involves detecting cancer in tissues on the basis of characteristic metabolite profiles using mass spectrometry imaging techniques. Nicole is excited to bring her knowledge and experience to a multidisciplinary team of clinicians and basic scientists who are developing metabolite databases to train the surgical mass spectrometry device,‘i-knife’, to be used intra-operatively in cancer surgery; a new tool expected to improve patient outcome by reducing positive margin rates.

Authorship: Nicole Morse (1), Martin Kaufmann (1), Kevin Yi Mi Ren (1), Kaci Carter (1), Seth Chitayat (1) Gabor Fichtinger (1), Zoltan Takats (2), John F. Rudan(2), David M. Berman(1), Sonal Varma(1)
(1) Queen's University, Kingston, Ontario, Canada (2) Imperial College London, London, UK

Short Abstract

Obtaining negative margins in breast cancer surgery is critical in preventing recurrence. We assessed performance of DESI in a simulated resection margin analysis in breast cancer, by imaging frozen sections, and by hematoxylin/eosin staining for histology correlation. Metabolites m/z 215 and m/z 863 were selectively abundant in non-neoplastic tissue and tumor tissue respectively. Furthermore, MSI based on the ratio of m/z 863/215 improved the ability to detect tumor in samples with smaller, more infiltrative nests. This work points to the potential of MSI based on ion intensity ratios to improve correlation between histology and MSI.

Long Abstract

Introduction: Obtaining negative margins in breast cancer surgeries is critical in preventing local recurrence. Re-operation rate due to positive margin is around 15% for lumpectomies, and could be improved by ancillary intraoperative tissue identification techniques. DESI MSI is an emerging technique capable of tissue characterization based on metabolite profiling. It can be applied to unstained frozen section slides to create tissue images based on the relative abundance of metabolites that topographically match the histology sections. We present a pilot study assessing DESI's ability to perform a simulated margin analysis in lumpectomies.

Methods: Fresh tumor samples with adjacent non-neoplastic tissue were collected from 10 lumpectomies with biopsy-proven invasive ductal carcinomas. Each tissue edge of the specimen was defined as a simulated margin. Unstained frozen section slides were subjected to DESI MSI, and subsequently stained by hematoxylin and eosin (H&E) for histologic correlation.

Results: A range of ions were observed to differentiate malignant and non-neoplastic tissue. Particularly, m/z 863 and m/z 215 were selectively abundant in malignant and non-neoplastic tissue respectively, and mass spectrometry images based on these ions were well-correlated with pathological assessment in cases with large tumor nests. However, images based on the ratio of m/z 863/215 improved pathological correlation with sections containing smaller tumor clusters at tumor margins, as well as in tumor sections where adjacent non-neoplastic tissue was not available for comparison.

Conclusions: Our findings demonstrate that DESI MSI based on the relative abundance ratio of selected metabolites in tumor versus non-neoplastic tissue has the potential to be an adjunct technique to histology for margin assessment. Additionally, it provides metabolic signatures to inform intra-operative margin assessment techniques including rapid evaporative ionization mass spectrometry (REIMS) which is currently under investigation.


References & Acknowledgements:

Acknowledgments: This work was supported by grants from OICR (to SV), and the Britton Smith Chair (to JR). We thank Waters Corporation for assistance with DESI method development.


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