Evidence map›Paper›PMID 26774260›Full record

ArticleJournal of translational medicine2016

Autoantibody signatures defined by serological proteome analysis in sera from patients with cholangiocarcinoma.

Mohammad Zahid Mustafa, Viet Hung Nguyen, François Le Naour, Eleonora De Martin, Elvire Beleoken, Catherine Guettier, Catherine Johanet, Didier Samuel, Jean-Charles Duclos-Vallee, Eric Ballot

Abstract read
In one paragraph

Article in Journal of translational medicine, 2016. 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
–field-weighted citation impact
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.

  1. Serological Proteome Analysis for Antigen Identification.Methods in molecular biology (Clifton, N.J.) · 2026
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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

10 authors.

Mohammad Zahid MustafaInserm, Unité 1193, Université Paris-Saclay, 94800, Villejuif, France. zunzah@gmail.com.
Viet Hung NguyenInserm, Unité 1193, Université Paris-Saclay, 94800, Villejuif, France. viet-hung.nguyen@inserm.fr.
François Le NaourInserm, Unité 1193, Université Paris-Saclay, 94800, Villejuif, France. francois.le-naour@inserm.fr.
Eleonora De MartinInserm, Unité 1193, Université Paris-Saclay, 94800, Villejuif, France. elenoira@hotmail.com.
Elvire BeleokenInserm, Unité 1193, Université Paris-Saclay, 94800, Villejuif, France. elvire_beleoken@yahoo.com.
Catherine GuettierInserm, Unité 1193, Université Paris-Saclay, 94800, Villejuif, France. catherine.guettier@bct.aphp.fr.
Catherine JohanetInserm, Unité 1193, Université Paris-Saclay, 94800, Villejuif, France. catherine.johanet@sat.aphp.fr.
Didier SamuelInserm, Unité 1193, Université Paris-Saclay, 94800, Villejuif, France. didier.samuel@pbr.aphp.fr.
Jean-Charles Duclos-ValleeInserm, Unité 1193, Université Paris-Saclay, 94800, Villejuif, France. jean-charles.duclos-vallee@pbr.aphp.fr.
Eric BallotInserm, Unité 1193, Université Paris-Saclay, 94800, Villejuif, France. eric.ballot@sat.aphp.fr.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe challenging diagnosis and poor prognosis of cholangiocarcinoma require the determination of biomarkers. Autoantibodies could be used in the clinic as diagnostic markers for the early detection of tumours. By proteomic approaches, several autoantibodies were proposed as potential markers. We tried in this study, to perform a serological proteome analysis, using various antigenic substrates, including tumours and human liver.

methodsSera from patients (n = 13) and healthy donors (n = 10) were probed on immunoblots performed using 2-dimensionally separated proteins from cholangiocarcinoma cell lines (CCLP1 and CCSW1), from the liver of healthy subject and interestingly, from tumour and adjacent non-tumour liver tissues from five patients with cholangiocarcinoma and tested with their corresponding serum. Spots of interest were identified using mass spectrometry and classified according gene ontology analysis.

resultsA comparison of the whole immunoblotting patterns given by cholangiocarcinoma sera against those obtained with normal control sera enabled the definition of 862 spots. Forty-five different proteins were further analysed, corresponding to (1) spots stained with more than four of 13 (30 %) sera tested with the CCLP1 or the CCSW1 cell line and with the normal liver, and (2) to spots immunoreactive with at least two of the five sera probed with their tumour and non-tumour counter-part of cholangiocarcinoma. Immunoreactive proteins with catalytic activity as molecular function were detected at rates of 93 and 64 % in liver from healthy subjects or cholangiocarcinoma non-tumour tissues respectively, compared to 43, 33, 33 % in tumour tissues, or CCSW1 and CCLP1 cell lines. A second pattern was represented by structural proteins with rates of 7 and 7 % in normal liver or non-tumour tissues compared to 14, 33 and 67 % in tumour tissue, CCSW1 or CCLP1 cell lines. Proteins with a binding function were detected at rates of 7 % in non-tumour tissue and 14 % in tumour tissue. Using the extracted tumour tissue, serotransferrin was targeted by all cholangiocarcinoma-related sera.

conclusionsImmunological patterns depended on the type of antigen substrate used; i.e. tumour versus non tumour specimens. Nevertheless, a combination of multiple autoantibodies tested with the most appropriate substrate might be more sensitive and specific for the diagnosis of cholangiocarcinoma.

Indexed as

AutoantibodiesBile Duct NeoplasmsCell Line, TumorCholangiocarcinomaElectrophoresis, Gel, Two-DimensionalElectrophoresis, Polyacrylamide GelGene OntologyHumansImmunoblottingLiverProteomeProteomicsReproducibility of ResultsAutoantibodiesProteome

Identifiers

PMID26774260
PMCPMC4715332

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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.