Evidence map›Paper›PMID 34679944›Full record

ArticleAnimals : an open access journal from MDPI2021

Serum Level of Tumor-Overexpressed AGR2 Is Significantly Associated with Unfavorable Prognosis of Canine Malignant Mammary Tumors.

Stephen Hsien-Chi Yuan, Shih-Chieh Chang, Yenlin Huang, Hao-Ping Liu

Open access · goldAbstract read
In one paragraph

Article in Animals : an open access journal from MDPI, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.4field-weighted citation impact, top 15% 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

5 citing papers in PubMed, 12 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Review
  5. 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

4 authors at 2 institutions in 1 country.

Stephen Hsien-Chi YuanDepartment of Veterinary Medicine, College of Veterinary Medicine, National Chung Hsing University, Taichung 40227, Taiwan.ORCID 0000-0001-8243-3704
Shih-Chieh ChangDepartment of Veterinary Medicine, College of Veterinary Medicine, National Chung Hsing University, Taichung 40227, Taiwan.
Yenlin HuangDepartment of Pathology, Chang Gung Memorial Hospital, Taoyuan 33378, Taiwan.
Hao-Ping LiuDepartment of Veterinary Medicine, College of Veterinary Medicine, National Chung Hsing University, Taichung 40227, Taiwan.ORCID 0000-0001-5915-5128
National Chung Hsing University · TWChang Gung Memorial Hospital · TW

Funding

College of Veterinary Medicine, National Chung Hsing University VMTH-CVM-109Ministry of Science and Technology, Taiwan MOST 109-2320-B-005-011-
6 · The paper itself

Abstract

Canine malignant mammary tumors (MMTs) are prevalent malignancy in intact female dogs with a high incidence of metastasis and recurrence. A current lack of easily accessible tumor biomarkers hinders a timely assessment of the disease outcome. We previously identified anterior gradient protein 2 (AGR2) with higher protein abundance in canine MMT tissues compared with normal counterparts. AGR2 is an endoplasmic reticulum-resident protein disulfide isomerase involved in the regulation of protein processing and also exists extracellularly via secretion to exert pro-oncogenic functions. In the present study, we validated overexpression of AGR2 in canine MMT tissues from 45 dogs using immunohistochemistry and immunoblotting, and assessed serum AGR2 levels in 81 dogs with MMTs and 21 benign cases using a competitive enzyme-linked immunosorbent assay (ELISA). Our data revealed that serum eAGR2 levels are significantly correlated with MMT progression (

Indexed as

AGR2caninemammary tumorsprognosisserumtumor metastasis

Identifiers

PMID34679944
PMCPMC8532596
OpenAlexW3205447974

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.