MALDI mass spectrometry imaging-Diagnostic pathways and metabolites for renal tumor entities

Background: Correct tumor subtyping of primary renal tumors is essential for treatment decision in daily routine. Most of the tumors can be classified on morphology alone. Nevertheless, some diagnoses are difficult and further investigations are needed for correct tumor subtyping. Beside 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 (FFPE) tissue specimens from clear cell renal cell carcinoma (ccRCC, n=552), papillary RCC (pRCC, n=122), chromophobe RCC (chRCC, n=108) and renal Oncocytoma (rO, n=71) were analyzed by high mass resolution matrix-assisted laser desorption/ionization (MALDI) fourier-transform ion cyclotron resonance (FT-ICR) mass spectrometry imaging (MSI). 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, glycerophospholipid 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 in biomarker detection.

Automated summary

In this study, high mass resolution matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) was used to classify and detect biomarkers for four common primary renal tumors. By analyzing tissue specimens, the metabolic pathways and profiles of different renal tumor subtypes were determined. This method has a high accuracy in tumor discrimination and can be a useful tool in differential diagnosis and biomarker detection.