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Review
. 2024 Apr:86:103068.
doi: 10.1016/j.copbio.2024.103068. Epub 2024 Feb 7.

Mass spectrometry imaging methods for visualizing tumor heterogeneity

Affiliations
Review

Mass spectrometry imaging methods for visualizing tumor heterogeneity

Kyle D Duncan et al. Curr Opin Biotechnol. 2024 Apr.

Abstract

Profiling spatial distributions of lipids, metabolites, and proteins in tumors can reveal unique cellular microenvironments and provide molecular evidence for cancer cell dysfunction and proliferation. Mass spectrometry imaging (MSI) is a label-free technique that can be used to map biomolecules in tumors in situ. Here, we discuss current progress in applying MSI to uncover molecular heterogeneity in tumors. First, the analytical strategies to profile small molecules and proteins are outlined, and current methods for multimodal imaging to maximize biological information are highlighted. Second, we present and summarize biological insights obtained by MSI of tumor tissue. Finally, we discuss important considerations for designing MSI experiments and several current analytical challenges.

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Conflict of interest statement

Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

Figure 1:
Figure 1:
Principle of mass spectrometry imaging for visualizing in situ molecular heterogeneity in tumor tissue.
Figure 2:
Figure 2:
General mass spectrometry imaging workflow. (A) A summary of sample preparation and analysis by MALDI and DESI, the two most commonly employed MSI techniques in tumor research. (B-C) An example of workflows for exploration of intratumor and intertumor heterogeneity. Based on hundreds to thousands of ions captured in a single MSI run, segmentation analysis outlines tumor regions with similar mass spectrum profiles (R1-R4 in the picture). These regions can be selectively extracted by laser capture microdissection and analyzed by traditional mass spectrometry techniques. The resulting MSI and LC-MS/MS data can then be used to compare regions with distinct spectral profiles within a tumor (B) or regions with similar spectral profiles between individual tumor samples (C).
Figure 3:
Figure 3:
Representative word cloud of lipids and metabolites that were detected in tumor samples by MSI techniques based on references [,–42,50,51,53,87]. The size of the word is scaled directly to the detection frequency, and each lipid or metabolite class (e.g., phosphatidylcholine) was only counted once per study.

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