Volume 64, Issue 24 e202502028
Communication

Integrating Ambient Ionization Mass Spectrometry Imaging and Spatial Transcriptomics on the Same Cancer Tissues to Identify RNA–Metabolite Correlations

Trevor M. Godfrey

Trevor M. Godfrey

Department of Surgery, Baylor College of Medicine, Houston, TX, 77030 USA

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Yasmin Shanneik

Yasmin Shanneik

Department of Surgery, Baylor College of Medicine, Houston, TX, 77030 USA

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Wanqiu Zhang

Wanqiu Zhang

Aspect Analytics NV, Genk, Belgium

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Thao Tran

Thao Tran

Aspect Analytics NV, Genk, Belgium

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Nico Verbeeck

Nico Verbeeck

Aspect Analytics NV, Genk, Belgium

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Nathan H. Patterson

Nathan H. Patterson

Aspect Analytics NV, Genk, Belgium

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Faith E. Jackobs

Faith E. Jackobs

Department of Surgery, Baylor College of Medicine, Houston, TX, 77030 USA

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Chandandeep Nagi

Chandandeep Nagi

Department of Pathology and Immunology, Baylor College of Medicine, Houston, TX, 77030 USA

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Maheshwari Ramineni

Maheshwari Ramineni

Department of Pathology and Immunology, Baylor College of Medicine, Houston, TX, 77030 USA

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Livia S. Eberlin

Corresponding Author

Livia S. Eberlin

Department of Surgery, Baylor College of Medicine, Houston, TX, 77030 USA

E-mail: [email protected]

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First published: 11 April 2025
Citations: 1

Graphical Abstract

Innovations in spatial omics have advanced disease research, but spatial transcriptomics (ST) and spatial metabolomics remain separate. We present a novel method integrating DESI-MSI spatial metabolomics and Visium-ST on the same tissue sections while preserving RNA quality and data integrity. Applied to breast and lung cancer tissue, this approach reveals new metabolite-transcript correlations in cancer regions, enhancing spatial multi-omics discoveries.

Abstract

Innovations in spatial omics technologies applied to human tissues have led to breakthrough discoveries in various diseases, including cancer. Two of these approaches—spatial transcriptomics and spatial metabolomics—have blossomed independently, fueled by technologies such as spatial transcriptomics (ST) and mass spectrometry imaging (MSI). Although powerful, these technologies only offer insights into the spatial distributions of restricted classes of molecules and have not yet been integrated to provide more holistic insights into biological questions. These techniques can be performed on adjacent serial sections from the same sample, but section-to-section variability can convolute data integration. We present a novel method combining desorption electrospray ionization mass spectrometry imaging (DESI-MSI) spatial metabolomics and Visium spatial transcriptomics on the same tissue sections. We show that RNA quality is maintained after performing DESI-MSI on a tissue under ambient conditions and that ST data is unperturbed following DESI-MSI. We demonstrate this workflow on human breast and lung cancer tissues and identify novel correlations between metabolites and mRNA transcripts in cancer-specific tissue regions.

Conflict of Interests

L.S.E. is an inventor in patents related to DESI-MS imaging technology owned by Purdue Research Foundation that were licensed to Waters Corporation and receives royalties from sales of the systems. W.Z., T.T., N.V., and N.H.P. are employees at Aspect Analytics NV. N.V. is a shareholder of Aspect Analytics NV.

Data Availability Statement

The data that support the findings of this study are openly available in Dataverse at https://doi.org/10.7910/DVN/GZFCWC, reference number 107910.

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