Recent advancements in Matrix Assisted Laser Desorption/Ionisation (MALDI) Mass Spectrometry Imaging (MSI) technology have enabled the analysis of formalin-fixed paraffin-embedded (FFPE) tissue samples, unlocking a wealth of new proteomic information and facilitating the possibility of performing studies with higher statistical power as well as multi-centric collaborations within the field of proteomics research. However, current methods used to analyse these specimens are often time-consuming and they need to be modified when applied to human tissues of different origin. Here we present a reproducible and time-effective method that could address these aforementioned issues and widen the applicability of this technology to a number of challenging tissue types. Additionally, tissue molecular images show high spatial resolution and a strong correlation with the morphological features, enabling the identification of tissue morphology using statistically derived visualisation, without any prior knowledge.
DE SIO, G., Smith, A., Galli, M., Garancini, M., Chinello, C., Bono, F., et al. (2015). A MALDI-Mass Spectrometry Imaging method applicable to different formalin-fixed paraffin-embedded human tissues. MOLECULAR BIOSYSTEMS, 11(6), 1507-1514 [10.1039/c4mb00716f].
A MALDI-Mass Spectrometry Imaging method applicable to different formalin-fixed paraffin-embedded human tissues
DE SIO, GABRIELEPrimo
;SMITH, ANDREW JAMESSecondo
;GALLI, MANUEL;CHINELLO, CLIZIA;PAGNI, FABIO
Penultimo
;MAGNI, FULVIOUltimo
2015
Abstract
Recent advancements in Matrix Assisted Laser Desorption/Ionisation (MALDI) Mass Spectrometry Imaging (MSI) technology have enabled the analysis of formalin-fixed paraffin-embedded (FFPE) tissue samples, unlocking a wealth of new proteomic information and facilitating the possibility of performing studies with higher statistical power as well as multi-centric collaborations within the field of proteomics research. However, current methods used to analyse these specimens are often time-consuming and they need to be modified when applied to human tissues of different origin. Here we present a reproducible and time-effective method that could address these aforementioned issues and widen the applicability of this technology to a number of challenging tissue types. Additionally, tissue molecular images show high spatial resolution and a strong correlation with the morphological features, enabling the identification of tissue morphology using statistically derived visualisation, without any prior knowledge.File | Dimensione | Formato | |
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