Vrana, Julie A.

The spleen is a commonly encountered specimen in surgical pathology. However, little is known about the incidence, morphologic pattern, and clinical features of spleens involved by amyloidosis. We retrospectively identified 69 spleen amyloid cases typed using a proteomics-based method between 2008 and 2020. The frequency of amyloid types, clinicopathologic features, and distribution of amyloid deposits were assessed. Four amyloid types were detected: immunoglobulin light chain (AL) (N=30; 43.5%); leukocyte chemotactic factor 2 amyloidosis (ALECT2) (N=30; 43.5%); amyloid A (AA) (N=8; 11.6%); and fibrinogen alpha (AFib) (N=1; 1.4%). The splenic amyloid showed 5 distinct distribution patterns: (1) diffuse pattern, exhibited by most AL cases; (2) red pulp pattern, exhibited by most ALECT2 cases; (3) multinodular pattern, seen in subsets of AA and AL-kappa cases; (4) mass-forming pattern, seen in the AFib case; and (5) vascular only, seen in a subset of AA cases. Atraumatic splenic rupture was the most common reason for splenectomy in AL cases, while most ALECT2 spleens were removed incidentally during an unrelated abdominal surgery. Splenomegaly was significantly more common in AA spleens than in AL or ALECT2 spleens and was often the reason for splenectomy in this group. In conclusion, splenic amyloid may be underrecognized as it is often an incidental finding. Although, as expected, many of the spleens were involved by AL amyloidosis, ALECT2 emerged as another common spleen amyloid type. Although the spleen amyloid types exhibited characteristic distribution patterns, proteomics-based typing is warranted as some morphologic overlap still exists. Awareness of ALECT2 as a major spleen amyloid type is important for appropriate diagnostic workup and patient management.

Abstract Aims Cardiac scintigraphy, a non-invasive technique for diagnosing ATTR cardiac amyloidosis, lacks specificity in patients with concomitant monoclonal gammopathy (up to 40% of cases). For these patients, amyloid type is often established by endomyocardial biopsy (EMB), which has clinical risk. This study aimed to investigate the frequency of ATTR in amyloid-positive tendon/synovium, urinary bladder, and prostate biopsies, sites for which prior biopsy specimens might exist for patients suspected of having cardiac amyloidosis, and, when available, determine the amyloid type concordance rate with other anatomic sites and provide clinical data regarding subsequent development of cardiac amyloidosis. Methods and results We queried our reference laboratory database of 19,298 amyloid specimens from myriad anatomic sites typed by mass spectrometry-based proteomics (LC-MS/MS) to investigate the frequency of ATTR amyloid in tendon/synovium, urinary bladder, and prostate. The amyloid type was ATTR in 104/138 (75.4%) tendon/synovium, 173/453 (38.0%) urinary bladder, and 27/81 (33.3%) prostate samples. Of 62 patients with available clinical data, 12 (19%) had bona fide ATTR cardiac amyloidosis prior to/concomitant with the non-cardiac site biopsy. Of the remaining 14 with follow-up, 8 developed bona fide and 2 probable cardiac amyloidosis; at last follow-up 4 had no evidence of cardiac amyloidosis. Fourteen of 16 patients (87.5%) for whom we typed both non-cardiac and cardiac sites had concordant amyloid types. There were 2 discordant cases (prostate = ASem1/heart = AL and urinary bladder = AL/heart = ATTR); only the latter is potentially clinically consequential. Conclusions In patients suspected of having cardiac amyloidosis based on cardiac scintigraphy, LC-MS/MS typing of Congophilic deposits in pre-existing biopsy specimens from non-cardiac sites may help establish the cardiac amyloid type, obviating the need for EMB. However, if the amyloid type identified in the non-cardiac site is not in keeping with other clinical features, then EMB for typing the cardiac amyloid might be indicated.

AimsTo characterise the clinicopathological features of amyloidosis due to EGF‐containing fibulin‐like extracellular matrix protein 1 (EFEMP1), a newly described amyloid type.Methods and resultsWe identified cases by searching the Mayo Clinic amyloid liquid chromatography and tandem mass spectrometry typing database for specimens with the universal amyloid signature proteins, abundant EFEMP1 spectra and absence of other specific amyloid precursor proteins. We also developed an immunohistochemical stain for EFEMP1 applicable to formalin‐fixed tissue sections and performed electron microscopy in one case. We identified 33 specimens from 32 patients with EFEMP1 amyloid. Most patients were female (91%) with a mean age of 75 years, and most specimens (94%) were from the bowel. EFEMP1 amyloid was incidentally identified in specimens biopsied/resected for a variety of clinical indications. In bowel specimens, EFEMP1 amyloid involved blood vessels and interstitium of the lamina propria, submucosa and/or muscularis propria. Although the EFEMP1 deposits were weakly to moderately Congo red‐positive with absent to weak birefringence, they were strongly positive for EFEMP1 by immunohistochemistry, had the characteristic fibrillar ultrastructure of amyloid and were readily identified by mass spectrometry.ConclusionsEFEMP1 amyloid is a recently described novel amyloid type that predominantly affects the bowel of elderly females. Because EFEMP1 amyloid is only weakly Congo red‐positive, it may be overlooked without a high index of suspicion. However, its characteristic microanatomical distribution is highlighted by immunohistochemistry and its identity is readily confirmed by mass spectrometry. Based on its distinctive features, we propose that EFEMP1 amyloidosis be considered a new amyloid type.

Abstract Abdominal subcutaneous fat aspiration is one of the most practical, sensitive and specific methods for the diagnosis of systemic amyloidosis. One limitation of this method, compared to more invasive tissue biopsy based approaches, remains the technical difficulties in further classification of the amyloidosis as commonly used methods, such as immunohistochemistry, are not readily applicable to fat aspiration specimens. To overcome these difficulties we developed a method using nano-flow liquid chromatography electrospray tandem mass spectrometry (LC-MS/MS) that could identify amyloid subtypes in freshly obtained Congo Red positive fat aspirate specimens with great accuracy. Abdominal subcutaneous fat aspirate specimens were obtained from 73 patients with clinical suspicion for systemic amyloidosis. One half of the specimen was stained with Congo red and used for diagnosis of amyloidosis and the other half was processed and enzyme digested for LC-MS/MS analysis. The resulting LC-MS/MS data was correlated to theoretical fragmentation patterns of tryptic peptide sequences from the Swissprot database using Scaffold (Mascot, Sequest, and X!Tandem search algorithms). Peptide identifications were accepted if they could be established at greater than 90.0% probability and protein identifications were accepted if they could be established at greater than 90.0% probability and contain at least 2 identified spectra. The identified proteins were subsequently examined for the presence or absence of amyloid related peptides. Of the 73 cases studied, 41 were positive for Congo red consistent with systemic amyloidosis. In Congo red positive cases, LC-MS/MS peptide profiles consistent with AL-lambda (28/31), AL-kappa (6/7), and ATTR (2/3) were observed. Only one case in the Congo red negative control group (31/32) gave a kappa light chain profile which was attributed to a high level of kappa in the serum (285 mg/dL). Of the 35 out of 41 cases of systemic amyloidosis successfully classified by LC-MS/MS, additional clinical and pathology data validating the amyloid type was available. In each of these cases the MS/MS results accurately predicted the amyloid type. In conclusion, LC-MS/MS proteomic analysis of abdominal subcutaneous fat aspiration specimens involved by amyloidosis provides a highly specific (97% specificity) and sensitive (>85% sensitivity) method for diagnosis and classification of amyloidosis. The method is rapid and readily applicable in a clinical setting and will greatly improve the clinical management of amyloidosis patients.

Abstract Background: Amyloidosis caused by immunoglobulin light chain (IGLC) deposition, so-called AL-type or primary amyloidosis, is the most common type of amyloidosis. It has been long believed that IGLC variable regions form the core of the AL-type amyloid deposits and peptides derived from IGLC constant region peptides are only occasionally integrated into this core. For this reason, the scientific effort to identify thge risk factors for development of AL amyloidosis and the biochemical characteristics amyloid deposits has focused on IGLC variable region derived proteins. To understand the peptide constituents of AL amyloidosis better, we undertook a comprehensive study of AL amyloidosis using a novel mass spectrometry based proteomic analysis approach. Methods: Paraffin embedded tissue from 100 cases of AL amyloidosis was studied. In each case amyloid type was previously established by clinical and pathological examination. Congo red stained paraffin sections were prepared and amyloid deposits were microdissected by laser microdissection microscopy. The microdissected tissue fragments were processed and trypsin digested into peptides. The peptides were analyzed by nano-flow liquid chromatography electrospray tandem mass spectrometry (LC-MS/MS). The resulting LC-MS/MS data were correlated to theoretical fragmentation patterns of tryptic peptide sequences from the Swissprot database using Scaffold (Mascot, Sequest, and X!Tandem search algorithms). Peptide identifications were accepted if they could be established at greater than 90.0% probability and protein identifications were accepted if they could be established at greater than 90.0% probability and contain at least 2 identified spectra. The identified proteins were subsequently examined for the presence or absence of amyloid related peptides. Results and Discussion: LC-MS/MS gave peptide profiles consistent with AL amyloidosis in each case. The analysis showed IGLC-lambda deposition in 66 cases and IGLC-kappa deposition in 34 of cases. In each case, LC MS/MS confirmed the previous clinicopathological diagnosis. Interestingly peptides representing IGLC constant region were present in each case. Using this LC-MS/MS methodology, theoretically it is possible to cover 78% of the IGLC-lambda and 87% IGLC-kappa constant regions. In our samples, the average coverage of the IGLC-lambda and IGLC-kappa constant regions were 40% (range 14–78%)and 55% (range 16–87%) respectively. Additionally, the distribution of the peptides suggested that in the majority of the cases whole of the IGLC constant region was deposited. LC MS/MS also identified IGLC-lambda variable region peptides in 37 of 66 cases and IGLC-kappa variable region peptides in 29 of 34 cases studied. The variable region coverage was more restricted and the peptides identified were frequently within the framework segments. It is likely that the peptides derived from CDR segments were present but not detected by the methodology as somatic hypermutation randomly alters the amino acid sequence in the CDR segments and such new sequences are not available in public databases used by algorithms for peptide identification. In the cases with the IGLC variable region hits, it was also possible to assign variable region family usage. IGLC-lambda cases frequently used IGLC-lambda variable region I, II and III families whereas, in IGLC-kappa cases, IGLC-kappa variable region I and III families dominated. Conclusions: AL amyloidosis can be accurately diagnosed using laser microdissection and LC-MS/MS based proteomic analysis in routine clinical specimens. AL amyloidosis invariably contains IGLC constant region peptides and, frequently, the whole of the constant region is deposited. This finding suggests that studies on molecular pathogenesis of amyloidosis should not only consider the IGLC-variable region but also the constant region. It is possible to identify IGLC variable region family usage in AL amyloidosis using LC MS/MS based proteomic analysis. In the clinical setting, this information may be helpful in predicting organ distribution and clinical outcome.

Abstract The management of systemic amyloidosis relies on the treatment of the underlying etiology and differs radically for different amyloid types. Therefore, given that at least 25 different proteins have been associated with amyloidosis, accurate identification of proteins deposited as amyloid fibrils is an important clinical problem. In this study, we describe a novel method that can characterize amyloid subtypes using laser microdissection (LMD) and mass spectrometry (MS) on routinely processed paraffin-embedded tissues. The study used 60 cases consisting of 16 transthyretin, 9 serum amyloid-associated protein, 20 immunoglobulin light chain lambda, 5 immunoglobulin light chain kappa, and 10 amyloid negative control samples. The biopsy specimens studied included heart, kidney, gastrointestinal tract, lung and decalcified bone marrow specimens. The amyloid type in all cases was previously characterized based on clinical findings, immunohistochemistry and, where indicated, by molecular testing for transthyretin mutations. Amyloid plaques were captured from an 10 micron paraffin section exhibiting positive Congo Red staining using LMD. Proteins were extracted, digested with trypsin and identified following MS/MS using the Mascot search algorithm analysis. MS correctly identified each of the 4 types of amyloidosis analyzed. Serum Amyloid P component and Apolipoprotein E were also identified as constituents of the amyloid deposition. The analysis was successful on all tissue types including decalcified bone marrow specimens and small biopsy specimens such as endomycardial biopsies and renal biopsies. The use of LMD from paraffin embedded biopsies and subsequent analysis by MS allows identification of the type of amyloid protein deposited with high specificity and sensitivity. This method promises to be a clinical test for accurate identification of amyloid proteins in routinely processed biopsy specimens and overcomes many of the specificity and sensitivity issues associated with current methods such as immunohistochemistry.

Abstract The amyloidoses are heterogeneous diseases associated with the deposition of insoluble proteins or peptides with a characteristic beta-diffraction pattern extracellularly. At the current time, over 27 different extracellular fibril proteins are known to cause disease in humans. Iatrogenic amyloidosis is a rare, often not sought diagnosis. On occasion, patients with drug induced amyloidosis can present with other systemic features reminiscent of systemic immunoglobulin-derived (AL) amyloidosis, and may present a diagnostic challenge. Treatment of the latter often involves chemotherapy and/or stem cell transplantation, while the former tends to remain localized and needs local therapy; thus accurate diagnosis is critical. To this end, proteomic analysis of amyloid tissue has proven to be an invaluable tool in amyloid typing. We have analyzed the biochemical composition of iatrogenic amyloid using laser capture/tandem mass spectrometry (LC-MS/MS)-based proteomic analysis in 52 cases of insulin and enfuvirtide (Fuzeon¨) associated amyloidosis. In brief, 10-μm-thick sections of formalin-fixed paraffin-embedded tissues were stained with Congo red. Congo red positively staining tissue as viewed with a fluorescent light source appeared bright red. Positive areas were dissected using laser microdissection to a volume of at least 60,000 μm2; three microdissections were analyzed for each case. The microdissected material was collected into 0.5-ml microcentrifuge tube caps containing 35 μL Tris/EDTA/0.002% Zwittergent buffer. Microdissected fragments were subjected to a heat-mediated antigen retrieval method (98C for 90minutes) before being denatured via sonication and subsequently digested into tryptic peptides overnight using 0.5ug of trypsin. The resulting digests were then analyzed with nanoflow LC-MS/MS. The MS/MS spectra of each case were matched against a composite protein sequence database using three different search algorithms (Sequest, X!Tandem, and Mascot). The composite database contained the human SwissProt entries but was also augmented with known immunoglobulin variant domains, known amyloidogenic mutations from literature, the enfuvirtide amino acid sequence, and common contaminants. Reversed protein sequences were appended to the database for estimating the false discovery rates of the identifications. The peptide identification results were filtered using Scaffold software (Proteome Software, Portland, OR) and then filtered peptides were assembled into protein identifications. Candidate proteins with at least one high-confident (probability of identification >90%) unique peptide identification and at least four MS/MS spectral matches were considered for clinical interpretation. For each case, we created a personalized proteomic profile that lists all the confident protein identifications in each of the microdissection along with their respective MS/MS spectral counts. The number of MS/MS spectra matching to a protein is considered as a semi-quantitative measure of its abundance. The most abundant amyloidogenic protein detected across all microdissections and as interpreted in the context of the clinical history is considered to be the amyloid subtype. Figure 1 shows the results of insulin amyloidosis. Figure 2 shows the results of enfuvirtide amyloidosis. Amyloid deposits are shown to be composed of the recombinant drug in addition to amyloid precursor proteins such as apolipoprotein A-I, A-IV, E and serum amyloid P (SAP).Figure 1. Insulin-associated amyloidosisFigure 1. Insulin-associated amyloidosisFigure 2Enfuvirtide (Fuzeon¨)-associated amyloidosisFigure 2. Enfuvirtide (Fuzeon¨)-associated amyloidosis In conclusion, we show the biochemical composition of all known drug-induced iatrogenic amyloidosis and provide the utility of proteomic analysis in elucidating amyloid subtyping for accurate diagnosis and management. Legend: A spectral count number of greater than 4 is significant. The green boxes denote protein identification at a probability of over 95%, and yellow 80-94%. In figure 1, insulin (# 2) and in figure 2, enfuvirtide (#5) are shown in abundance, additionally other amyloid precursors such as apolipoproteins A-IV, E, A-I and SAP are also seen. Disclosures: No relevant conflicts of interest to declare.