Aims: Identification and characterisation of monoclonal gammopathies of renal significance (MGRS) is critical for therapeutic purposes. Amyloidosis represents one of the most common forms of MGRS, and renal biopsy remains the gold standard for their classification, although mass spectrometry has shown greater sensitivity in this area. Methods: In the present study, a new in situ proteomic technique, matrix-assisted laser desorption/ionisation mass spectrometry imaging (MALDI-MSI), is investigated as an alternative to conventional laser capture microdissection MS for the characterisation of amyloids. MALDI-MSI was performed on 16 cases (3 lambda light chain amyloidosis (AL), 3 AL kappa, 3 serum amyloid A amyloidosis (SAA), 2 lambda light chain deposition disease (LCDD), 2 challenging amyloid cases and 3 controls). Analysis began with regions of interest labelled by the pathologist, and then automatic segmentation was performed. Results: MALDI-MSI correctly identified and typed cases with known amyloid type (AL kappa, AL lambda and SAA). A 'restricted fingerprint' for amyloid detection composed of apolipoprotein E, serum amyloid protein and apolipoprotein A1 showed the best automatic segmentation performance (area under the curve >0.7). Conclusions: MALDI-MSI correctly assigned minimal/challenging cases of amyloidosis to the correct type (AL lambda) and identified lambda light chains in LCDD cases, highlighting the promising role of MALDI-MSI for amyloid typing.

Spatial resolution of renal amyloid deposits through MALDI-MSI: a combined digital and molecular approach to monoclonal gammopathies / Bindi, Greta; Smith, Andrew; Oliveira, Glenda; Eccher, Albino; Vatrano, Simona; Alberici, Federico; Cazzaniga, Giorgio; Galimberti, Stefania; Capitoli, Giulia; Magni, Fulvio; Pagni, Fabio; L'Imperio, Vincenzo. - In: JOURNAL OF CLINICAL PATHOLOGY. - ISSN 0021-9746. - Online ahead of print:Feb 22(2023), pp. 1-10. [10.1136/jcp-2023-208790]

Spatial resolution of renal amyloid deposits through MALDI-MSI: a combined digital and molecular approach to monoclonal gammopathies

Eccher, Albino;
2023

Abstract

Aims: Identification and characterisation of monoclonal gammopathies of renal significance (MGRS) is critical for therapeutic purposes. Amyloidosis represents one of the most common forms of MGRS, and renal biopsy remains the gold standard for their classification, although mass spectrometry has shown greater sensitivity in this area. Methods: In the present study, a new in situ proteomic technique, matrix-assisted laser desorption/ionisation mass spectrometry imaging (MALDI-MSI), is investigated as an alternative to conventional laser capture microdissection MS for the characterisation of amyloids. MALDI-MSI was performed on 16 cases (3 lambda light chain amyloidosis (AL), 3 AL kappa, 3 serum amyloid A amyloidosis (SAA), 2 lambda light chain deposition disease (LCDD), 2 challenging amyloid cases and 3 controls). Analysis began with regions of interest labelled by the pathologist, and then automatic segmentation was performed. Results: MALDI-MSI correctly identified and typed cases with known amyloid type (AL kappa, AL lambda and SAA). A 'restricted fingerprint' for amyloid detection composed of apolipoprotein E, serum amyloid protein and apolipoprotein A1 showed the best automatic segmentation performance (area under the curve >0.7). Conclusions: MALDI-MSI correctly assigned minimal/challenging cases of amyloidosis to the correct type (AL lambda) and identified lambda light chains in LCDD cases, highlighting the promising role of MALDI-MSI for amyloid typing.
2023
Online ahead of print
Feb 22
1
10
Spatial resolution of renal amyloid deposits through MALDI-MSI: a combined digital and molecular approach to monoclonal gammopathies / Bindi, Greta; Smith, Andrew; Oliveira, Glenda; Eccher, Albino; Vatrano, Simona; Alberici, Federico; Cazzaniga, Giorgio; Galimberti, Stefania; Capitoli, Giulia; Magni, Fulvio; Pagni, Fabio; L'Imperio, Vincenzo. - In: JOURNAL OF CLINICAL PATHOLOGY. - ISSN 0021-9746. - Online ahead of print:Feb 22(2023), pp. 1-10. [10.1136/jcp-2023-208790]
Bindi, Greta; Smith, Andrew; Oliveira, Glenda; Eccher, Albino; Vatrano, Simona; Alberici, Federico; Cazzaniga, Giorgio; Galimberti, Stefania; Capitoli, Giulia; Magni, Fulvio; Pagni, Fabio; L'Imperio, Vincenzo
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11380/1317468
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