Implementation and evaluation of amyloidosis subtyping by laser-capture microdissection and tandem mass spectrometry

Peter Mollee, Samuel Boros, Dorothy Loo, Jayde E. Ruelcke, Vanessa A. Lakis, Kim-Anh Lê Cao, Patricia Renaut, Michelle M. Hill

Correct identification of the amyloidosis-causing protein is crucial for clinical management. Recently the Mayo Clinic reported laser-capture microdissection (LCM) with liquid chromatography-coupled tandem mass spectrometry (MS/MS) as a new diagnostic tool for amyloid diagnosis. Here, we report an independent implementation of this proteomic diagnostics method at the Princess Alexandra Hospital Amyloidosis Centre in Brisbane, Australia. From 2010 to 2014, 138 biopsies received from 35 different organ sites were analysed by LCM-MS/MS using Congo Red staining to visualise amyloid deposits. There was insufficient tissue in the block for LCM for 7 cases. An amyloid forming protein was ultimately identified in 121 out of 131 attempted cases (94 %). Of the 121 successful cases, the Mayo Clinic amyloid proteomic signature (at least two of Serum Amyloid P, ApoE and ApoA4) was detected in 92 (76 %). Low levels of additional amyloid forming proteins were frequently identified with the main amyloid forming protein, which may reflect co-deposition of fibrils. Furthermore, vitronectin and clusterin were frequently identified in our samples. Adding vitronectin to the amyloid signature increases the number of positive cases, suggesting a potential 4th protein for the signature. In terms of clinical impact, amyloid typing by immunohistochemistry was attempted in 88 cases, reported as diagnostic in 39, however, 5 were subsequently revealed by proteomic analysis to be incorrect. Overall, the referring clinician's diagnosis of amyloid subtype was altered by proteomic analysis in 24 % of cases. While LCM-MS/MS was highly robust in protein identification, clinical information was still required for subtyping, particularly for systemic versus localized amyloidosis. This study reports the independent implementation and evaluation of a proteomics-based diagnostic for amyloidosis subtyping. Our results support LCM-MS/MS as a powerful new diagnostic technique for amyloidosis, but also identified some challenges and further development opportunities.