Evidence map›Paper›PMID 31208374›Full record

ArticleBMC cancer2019

Exploring serum and immunoglobulin G N-glycome as diagnostic biomarkers for early detection of breast cancer in Ethiopian women.

Abrha G Gebrehiwot, Daniel Seifu Melka, Yimenashu Mamo Kassaye, Tufa Gemechu, Wajana Lako, Hiroshi Hinou, Shin-Ichiro Nishimura

Open access · goldAbstract read
In one paragraph

Article in BMC cancer, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed, 2 pooled it
2.7field-weighted citation impact, top 9% 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

26 citing papers in PubMed, 2 syntheses or guidelines pooled it, 50 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

7 authors at 2 institutions in 2 countries.

Abrha G GebrehiwotFaculty of Advanced Life Science and Graduate School of Life Science, Hokkaido University, N21, W11, Kita-ku, Sapporo, 001-0021, Japan.
Daniel Seifu MelkaDepartment of Biochemistry, School of Medicine, Addis Ababa University, Addis Ababa, Ethiopia.
Yimenashu Mamo KassayeDepartment of Biochemistry, School of Medicine, Addis Ababa University, Addis Ababa, Ethiopia.
Tufa GemechuDepartment of Pathology, School of Medicine, Addis Ababa University, Addis Ababa, Ethiopia.
Wajana LakoDepartment of Pathology, School of Medicine, Addis Ababa University, Addis Ababa, Ethiopia.
Hiroshi HinouFaculty of Advanced Life Science and Graduate School of Life Science, Hokkaido University, N21, W11, Kita-ku, Sapporo, 001-0021, Japan.
Shin-Ichiro NishimuraFaculty of Advanced Life Science and Graduate School of Life Science, Hokkaido University, N21, W11, Kita-ku, Sapporo, 001-0021, Japan. shin@sci.hokudai.ac.jp.ORCID http://orcid.org/0000-0002-6608-8418
Addis Ababa University · ETHokkaido University · JP

Funding

Japanese Ministry of Education and Science 25220206Japan Science and Technology Agency core-to-core program B
6 · The paper itself

Abstract

backgroundAlterations in protein glycosylation patterns have potentially been targeted for biomarker discovery in a wide range of diseases including cancer. Although there have been improvements in patient diagnosis and survival for breast cancer (BC), there is no clinically validated serum biomarker for its early diagnosis. Here, we profiled whole serum and purified Immunoglobulin G (IgG) fraction N-glycome towards identification of non-invasive glycan markers of BC.

methodsWe employed a comprehensive glycomics approach by integrating glycoblotting-based glycan purification with MALDI-TOF/MS based quantitative analysis. Sera of BC patients belonging to stages I-IV and normal controls (NC) were collected from Ethiopian women during 2015-2016. IgG was purified by affinity chromatography using protein G spin plate and further subjected to glycoblotting for glycan release. Mass spectral data were further processed and evaluated rigorously, using various bioinformatics and statistical tools.

resultsOut of 35 N-glycans that were significantly up-regulated in the sera of all BC patients compared to the NC, 17 complex type N-glycans showed profound expression abundance and diagnostic potential (AUC = 0.8-1) for the early stage (I and II) BC patients. Most of these glycans were core-fucosylated, multiply branched and sialylated structures, whose abundance has been strongly associated with greater invasive and metastatic potential of cancer. N-glycans quantified form IgG confirmed their abundance in BC patients, of which two core-fucosylated and agalactosylated glycans (m/z 1591, 1794) could specifically distinguish (AUC = 0.944 and 0.921, p ≤ 0.001) stage II patients from NC. Abundance of such structural features in IgG is associated with a decrease in its immunosuppressive potential towards tumor cells, which in part may correlate with the aggressive nature of BC commonly noticed in black population.

conclusionsOur comprehensive study has addressed for the first time both whole serum and IgG N-glycosylation signatures of native black women suffering from BC and revealed novel glyco-biomarkers with marked overexpression and distinguishing ability at early stage patients. Further studies on direct identification of the intact glycoproteins using a glycoprteomics approach will provide a deeper understanding of specific biomarkers towards their clinical utility.

Indexed as

Early Detection of CancerAdultBiomarkers, TumorBreast NeoplasmsEthiopiaFemaleGlycomicsGlycoproteinsGlycosylationHumansImmunoglobulin GMiddle AgedNeoplasm StagingPolysaccharidesReproducibility of ResultsROC CurveBiomarkers, TumorGlycoproteinsglycosylated IgGImmunoglobulin GPolysaccharidesBreast cancerEarly stage biomarkerGlycoblottingIgGN-glycanSerum

Identifiers

PMID31208374
PMCPMC6580580
OpenAlexW2949476748

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.