Erlmeier, F.* ; Sun, N. ; Shen, J. ; Feuchtinger, A. ; Buck, A. ; Prade, V.M. ; Kunzke, T. ; Schraml, P.* ; Moch, H.* ; Autenrieth, M.* ; Weichert, W.* ; Hartmann, A.* ; Walch, A.K.
MALDI mass spectrometry imaging-Diagnostic pathways and metabolites for renal tumor entities.
Oncology 101, 126-133 (2022)
Background: Correct tumor subtyping of primary renal tumors is essential for treatment decision in daily routine. Most of the tumors can be classified based on morphology alone. Nevertheless, some diagnoses are difficult, and further investigations are needed for correct tumor subtyping. Besides histochemical investigations, high-mass-resolution matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) can detect new diagnostic biomarkers and hence improve the diagnostic. Patients and Methods: Formalin-fixed paraffin embedded tissue specimens from clear cell renal cell carcinoma (ccRCC, n = 552), papillary renal cell carcinoma (pRCC, n = 122), chromophobe renal cell carcinoma (chRCC, n = 108), and renal oncocytoma (rO, n = 71) were analyzed by high-mass-resolution MALDI fourier-transform ion cyclotron resonance (FT-ICR) MSI. The SPACiAL pipeline was executed for automated co-registration of histological and molecular features. Pathway enrichment and pathway topology analysis were performed to determine significant differences between RCC subtypes. Results: We discriminated the four histological subtypes (ccRCC, pRCC, chRCC, and rO) and established the subtype-specific pathways and metabolic profiles. rO showed an enrichment of pentose phosphate, taurine and hypotaurine, glycerophospholipid, amino sugar and nucleotide sugar, fructose and mannose, glycine, serine, and threonine pathways. ChRCC is defined by enriched pathways including the amino sugar and nucleotide sugar, fructose and mannose, glycerophospholipid, taurine and hypotaurine, glycine, serine, and threonine pathways. Pyrimidine, amino sugar and nucleotide sugar, glycerophospholipids, and glutathione pathways are enriched in ccRCC. Furthermore, we detected enriched phosphatidylinositol and glycerophospholipid pathways in pRCC. Conclusion: In summary, we performed a classification system with a mean accuracy in tumor discrimination of 85.13%. Furthermore, we detected tumor-specific biomarkers for the four most common primary renal tumors by MALDI-MSI. This method is a useful tool in differential diagnosis and biomarker detection.
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Publication type
Article: Journal article
Document type
Scientific Article
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Keywords
Chromophobe Renal Cell Carcinoma ; Clear Cell Renal Cell Carcinoma ; Mass Spectrometry Imaging ; Metabolomics ; Papillary Renal Cell Carcinoma ; Renal Oncocytoma
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Language
english
Publication Year
2022
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2022
ISSN (print) / ISBN
0030-2414
e-ISSN
1423-0232
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Volume: 101,
Issue: 2,
Pages: 126-133
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Karger
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Peer reviewed
POF-Topic(s)
30205 - Bioengineering and Digital Health
30505 - New Technologies for Biomedical Discoveries
Research field(s)
Enabling and Novel Technologies
PSP Element(s)
G-500390-001
A-630600-001
Grants
Swiss National Science Foundation (SNSF) European Commission
German Research Foundation (DFG)
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Erfassungsdatum
2022-12-20