Evidence map›Paper›PMID 34428239›Full record

ArticlePloS one2021

Immunohistochemical typing of amyloid in fixed paraffin-embedded samples by an automatic procedure: Comparison with immunofluorescence data on fresh-frozen tissue.

Antonella Barreca, Emanuel Bottasso, Francesca Veneziano, Manuela Giarin, Alberto Nocifora, Nadia Martinetti, Angelo Attanasio, Luigi Biancone, Giulia Benevolo, Dario Roccatello and 3 more

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
2.1field-weighted citation impact, top 12% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed, 26 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors at 4 institutions in 1 country.

Antonella BarrecaPathology Unit, City of Health and Science Hospital, Turin, Italy.ORCID 0000-0003-3566-1995
Emanuel BottassoDepartment of Medical Sciences, University of Turin, Turin, Italy.
Francesca VenezianoPathology Unit, City of Health and Science Hospital, Turin, Italy.
Manuela GiarinPathology Unit, City of Health and Science Hospital, Turin, Italy.ORCID 0000-0002-0900-5444
Alberto NociforaDepartment of Oncology, University of Turin, Turin, Italy.
Nadia MartinettiPathology Unit, City of Health and Science Hospital, Turin, Italy.
Angelo AttanasioPathology Unit, City of Health and Science Hospital, Turin, Italy.
Luigi BianconeDepartment of Medical Sciences, University of Turin, Turin, Italy.
Giulia BenevoloDivision of Hematology, Città della Salute e della Scienza Hospital, Turin, Italy.
Dario RoccatelloCMID, Coordinating Center of the Network for Rare Diseases of Piedmont and Aosta Valley, and Nephrology and Dialysis Unit (ERK-net Member), San Giovanni Bosco Hub Hospital and University of Turin, Turin, Italy.
Paola CassoniPathology Unit, City of Health and Science Hospital, Turin, Italy.
Mauro G PapottiPathology Unit, City of Health and Science Hospital, Turin, Italy.
Amyloidosis Group of the “Rete Interregionale Piemonte e Valle d’Aosta per le Malattie Rare”
Piedmont Reference Center for Epidemiology and Cancer Prevention · ITAzienda Ospedaliera Citta' della Salute e della Scienza di Torino · ITUniversity of Turin · ITOspedale San Giovanni Bosco · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Amyloidosis comprises a spectrum of disorders characterized by the extracellular deposition of amorphous material, originating from an abnormal serum protein. The typing of amyloid into its many variants represents a pivotal step for a correct patient management. Several methods are currently used, including mass spectrometry, immunofluorescence, immunohistochemistry, and immunogold labeling. The aim of the present study was to investigate the accuracy and reliability of immunohistochemistry by means of a recently developed amyloid antibody panel applicable on fixed paraffin-embedded tissues in an automated platform. Patients with clinically and pathologically proven amyloidosis were divided into two cohorts: a pilot one, which included selected amyloidosis cases from 2009 to 2018, and a retrospective one (comprising all consecutive amyloidosis cases analyzed between November 2018 and May 2020). The above-referred panel of antibodies for amyloid classification was tested in all cases using an automated immunohistochemistry platform. When fresh-frozen material was available, immunofluorescence was also performed. Among 130 patients, a total of 143 samples from different organs was investigated. They corresponded to 51 patients from the pilot cohort and 79 ones from the retrospective cohort. In 82 cases (63%), fresh-frozen tissue was tested by immunofluorescence, serving to define amyloid subtype only in 30 of them (36.6%). On the contrary, the automated immunohistochemistry procedure using the above-referred new antibodies allowed to establish the amyloid type in all 130 cases (100%). These included: ALλ (n = 60, 46.2%), ATTR (n = 29, 22.3%), AA (n = 19, 14.6%), ALκ (n = 18, 13.8%), ALys (n = 2, 1.5%), and Aβ2M amyloidosis (n = 2, 1.5%). The present immunohistochemistry antibody panel represents a sensitive, reliable, fast, and low-cost method for amyloid typing. Since immunohistochemistry is available in most pathology laboratories, it may become the new gold standard for amyloidosis classification, either used alone or combined with mass spectrometry in selected cases.

Indexed as

ProteomicsAdultAgedAged, 80 and overAmyloidAmyloidogenic ProteinsAmyloidosisFemaleFluorescent Antibody TechniqueHumansMaleMass SpectrometryMiddle AgedParaffin EmbeddingAmyloidAmyloidogenic Proteins

Identifiers

PMID34428239
PMCPMC8384180
OpenAlexW3194558309

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.