Evidence map›Paper›PMID 26272389›Full record

ArticleScientific reports2015

Generation of monoclonal antibodies against MGA and comparison of their application in breast cancer detection by immunohistochemistry.

Cuimi Duan, Xiqin Yang, Xuhui Zhang, Jiannan Feng, Zhiqiang Liu, Haiping Que, Heather Johnson, Yanfeng Zhao, Yawen Fan, Yinglin Lu and 4 more

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.2field-weighted citation impact, top 45% 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

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. Article
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

14 authors at 2 institutions in 1 country.

Cuimi DuanDepartment of Bio-diagnosis, Institute of Basic Medical Sciences, 27, Taiping Road, Beijing, 100850, China.
Xiqin YangDepartment of Bio-diagnosis, Institute of Basic Medical Sciences, 27, Taiping Road, Beijing, 100850, China.
Xuhui ZhangDepartment of Bio-diagnosis, Institute of Basic Medical Sciences, 27, Taiping Road, Beijing, 100850, China.
Jiannan FengDepartment of Immunology, Institute of Basic Medical Sciences, 27, Taiping Road, Beijing, 100850, China.
Zhiqiang LiuDepartment of Bio-diagnosis, Institute of Basic Medical Sciences, 27, Taiping Road, Beijing, 100850, China.
Haiping QueDepartment of Bio-diagnosis, Institute of Basic Medical Sciences, 27, Taiping Road, Beijing, 100850, China.
Heather JohnsonOlympia Diagnostics, Inc. Sunnyvale, CA 94086, USA.
Yanfeng ZhaoDepartment of Bio-diagnosis, Institute of Basic Medical Sciences, 27, Taiping Road, Beijing, 100850, China.
Yawen FanDepartment of Bio-diagnosis, Institute of Basic Medical Sciences, 27, Taiping Road, Beijing, 100850, China.
Yinglin LuDepartment of Bio-diagnosis, Institute of Basic Medical Sciences, 27, Taiping Road, Beijing, 100850, China.
Heqiu ZhangDepartment of Bio-diagnosis, Institute of Basic Medical Sciences, 27, Taiping Road, Beijing, 100850, China.
Yan HuangAffiliated 307 Hospital, Beijing, 100071, China.
Bingshui XiuDepartment of Bio-diagnosis, Institute of Basic Medical Sciences, 27, Taiping Road, Beijing, 100850, China.
Xiaoyan FengDepartment of Bio-diagnosis, Institute of Basic Medical Sciences, 27, Taiping Road, Beijing, 100850, China.
Institute of Basic Medical Sciences of the Chinese Academy of Medical Sciences307th Hospital of Chinese People’s Liberation Army · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Mammaglobin A (MGA) is an organ specific molecular biomarker for metastatic breast cancer diagnosis. However, there are still needs to develop optimal monoclonal antibodies (mAbs) to detect MGA expression in breast carcinoma by immunohistochemistry. In this study, we first generated mAbs against MGA. Then, we used epitope prediction and computer-assisted structural analysis to screen five dominant epitopes and identified mAbs against five epitopes. Further immunohistochemical analysis on 42 breast carcinoma specimens showed that MHG1152 and MGD785 had intensive staining mainly in membrane, while CHH11617, CHH995 and MJF656 had more intensive staining within the cytoplasm. MGA scoring results showed that MJF656 had the highest rate (92.8%) of positive staining among five mAbs, including higher staining intensity when compared with that of MHG1152 (p < 0.01) and CHH995 (p < 0.05) and the highest the mean percentage of cells stained among mAbs. Furthermore, we analyzed the relationship of positive staining rate by mAbs with patient clinical characteristics. The results suggest that MJF656 was able to detect MGA expression, especially in early clinical stage, low grade and lymph node metastasis-negative breast carcinoma. In conclusion, our study generated five mAbs against MGA and identified the best candidate for detection of MGA expression in breast cancer tissues.

Indexed as

AdultAgedAged, 80 and overAnimalsAntibodies, MonoclonalBiomarkers, TumorBreast NeoplasmsEpitope MappingFemaleHumansImmunoassayMaleMammaglobin AMiceMice, Inbred BALB CMiddle AgedAntibodies, MonoclonalBiomarkers, TumorMammaglobin A

Identifiers

PMID26272389
PMCPMC4536492
OpenAlexW1429541881

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.