Evidence map›Paper›PMID 34257587›Full record

ArticlePathology oncology research : POR2021

Estrogen Aggravates Tumor Growth in a Diffuse Gastric Cancer Xenograft Model.

Sunyi Lee, Kyoung Mee Kim, Seung Yeon Lee, Joohee Jung

Open access · goldAbstract read
In one paragraph

Article in Pathology oncology research : POR, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 pooled it
2.3field-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, 1 synthesis or guideline pooled it, 17 citations in OpenAlex.

  1. Pooled it
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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

4 authors at 1 institution in 1 country.

Sunyi LeeDuksung Innovative Drug Center, Duksung Women's University, Seoul, Korea.
Kyoung Mee KimDuksung Innovative Drug Center, Duksung Women's University, Seoul, Korea.
Seung Yeon LeeCollege of Pharmacy, Duksung Women's University, Seoul, Korea.
Joohee JungDuksung Innovative Drug Center, Duksung Women's University, Seoul, Korea.
Duksung Women's University · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Gastric cancer has the fifth-highest incidence rate and is the third leading cause of cancer-related deaths worldwide. The incidence of gastric cancer is higher in men than in women, but for the diffuse types of gastric cancer, the trend is opposite. Estrogen is considered the prime culprit behind these differences. Nevertheless, the action of estrogen in gastric cancers remains unclear. In this study, we investigated the effect of estrogen on diffuse-type gastric cancer. Human female diffuse gastric cancer SNU-16 cells were transplanted into male and female mice to analyze the effect of endogenous estrogen on tumor growth. Furthermore, the effect of exogenous estrogen was evaluated in ovariectomized mice. Expressed genes were compared between female and male xenograft models using RNA sequencing analysis. Furthermore, human gene expression omnibus databases were utilized to examine the effect of our target genes on overall survival. SNU-16-derived tumor growth was faster in female mice than in male mice. In total RNA sequencing, interferon gamma receptor 2 (

Indexed as

TranscriptomeAnimalsApoptosisBiomarkers, TumorCell ProliferationEstrogensFemaleGene Expression Regulation, NeoplasticHumansMaleMiceMice, NudeStomach NeoplasmsTumor Cells, CulturedXenograft Model Antitumor AssaysBiomarkers, TumorEstrogenscancer xenograft modeldiffuse gastric cancerestrogenovariectomized miceSUN-16 cells

Identifiers

PMID34257587
PMCPMC8262185
OpenAlexW3155108110

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.