Evidence map›Paper›PMID 40820122›Full record

ArticleAnalytical and bioanalytical chemistry2025

Evaluating rapid evaporative ionization mass spectrometry profiles of human breast cancer cells using a 3D in vitro assay.

Rachel E Rubino, Martin Kaufmann, Amoon Jamzad, Natasha Iaboni, Kevin Yi Mi Ren, Jian Yu, Haidy Metwally, Manuela Kunz, John F Rudan, Parvin Mousavi and 3 more

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Article in Analytical and bioanalytical chemistry, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

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No citing paper in PubMed yet.

4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Rachel E Rubino *Division of Cancer Biology & Genetics, Queen's Sinclair Cancer Research Institute, 10 Stuart Street, Kingston, ON, K7L 3N6, Canada.
Martin Kaufmann *Department of Surgery, Kingston Health Sciences Centre, Kingston, ON, Canada.
Amoon JamzadSchool of Computing, Queen's University, Kingston, ON, Canada.
Natasha IaboniDepartment of Pathology & Molecular Medicine, Queen's University, and Kingston Health Sciences Centre, Kingston, ON, Canada.
Kevin Yi Mi RenDepartment of Pathology & Molecular Medicine, Queen's University, and Kingston Health Sciences Centre, Kingston, ON, Canada.
Jian YuDepartment of Chemistry, Queen's University, Kingston, ON, Canada.
Haidy MetwallyDepartment of Chemistry, Queen's University, Kingston, ON, Canada.
Manuela KunzSchool of Computing, Queen's University, Kingston, ON, Canada.
John F RudanDepartment of Surgery, Kingston Health Sciences Centre, Kingston, ON, Canada. john.rudan@kingstonhsc.ca.
Parvin MousaviSchool of Computing, Queen's University, Kingston, ON, Canada.
Gabor FichtingerSchool of Computing, Queen's University, Kingston, ON, Canada.
Richard OleschukDepartment of Chemistry, Queen's University, Kingston, ON, Canada.
Christopher J B NicolDivision of Cancer Biology & Genetics, Queen's Sinclair Cancer Research Institute, 10 Stuart Street, Kingston, ON, K7L 3N6, Canada. nicolc@queensu.ca.ORCID http://orcid.org/0000-0002-3818-0145

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Rapid evaporative ionization mass spectrometry (REIMS) enables near real-time sampling and classification of tissues on the basis of lipid and small molecule profiles. Because samples are ablated during REIMS, validation of mass spectra by assignment of class labels using gold-standard methods remains challenging. Further, determining the number of abnormal cells within a mixture of normal cells by REIMS remains an elusive but critical parameter when evaluating the utility of REIMS for use in clinical settings. To address this, we developed a three-dimensional assay based on fluorescently labelled human breast cell lines, MCF-10A (pseudo-normal) and MDA-MB-231 (malignant), embedded in matrigel cubes that enables calculation of cell numbers ablated by REIMS by measuring fluorescence before and after REIMS sampling. We observed a reasonably uniform distribution of cells throughout the matrigel matrix, which yielded REIMS spectra rich in complex glycerophospholipids resembling solid tissues and cell pellets. A non-linear relationship between signal intensity and the number of cells ablated was observed. We trained multivariate models using 10% increments of MDA-MB-231 cells mixed with MCF-10A, and blindly tested the models on separate cubes containing 1-100% MDA-MB-231s. Percent difference from target MDA-MB-231 cell composition was within 34% for cubes containing as little as 5% MDA-MB-231 cells. Overall, our study highlights how a simple 3D in vitro approach may help reveal the quantitative potential of mass spectral profiling methods such as REIMS to assist with validating REIMS spectra containing mixtures of different cell lines. This assay platform may help calibrate REIMS-based methods to recognize specific cell type mixtures encountered at surgical resection margins.

Indexed as

Breast NeoplasmsCell Culture Techniques, Three DimensionalMass SpectrometryCell Line, TumorCollagenDrug CombinationsFemaleHumansLamininProteoglycansCollagenDrug CombinationsLamininmatrigelProteoglycansCell cultureGlycerophospholipidsHuman breast cancer cell linesIn vitro assayMachine learningRapid evaporative ionization mass spectrometry (REIMS)

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.