Evidence map›Paper›PMID 30233209›Full record

ArticleOncoTargets and therapy2018

Absence of AIF1L contributes to cell migration and a poor prognosis of breast cancer.

Peipei Liu, Wenhui Li, Yuanyuan Hu, Youhong Jiang

Open access · goldAbstract read
In one paragraph

Article in OncoTargets and therapy, 2018. 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
0.4field-weighted citation impact, top 39% 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, 15 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

4 authors at 1 institution in 1 country.

Peipei LiuMolecular Oncology Laboratory of Cancer Research Institute, The First Hospital of China Medical University, Shenyang, People's Republic of China, jiangyouhong2000@aliyun.com.
Wenhui LiGastrointestinal Onco-Pathology Laboratory of Cancer Institute, The First Hospital of China Medical University, Shenyang 110001, People's Republic of China.
Yuanyuan HuMolecular Oncology Laboratory of Cancer Research Institute, The First Hospital of China Medical University, Shenyang, People's Republic of China, jiangyouhong2000@aliyun.com.
Youhong JiangMolecular Oncology Laboratory of Cancer Research Institute, The First Hospital of China Medical University, Shenyang, People's Republic of China, jiangyouhong2000@aliyun.com.
First Hospital of China Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundBreast cancer is the most common fatal cancer in women worldwide. Previous studies have demonstrated that allograft inflammatory factor 1 like (AIF1L) plays a key role in mammary tumorigenesis, although the mechanism involved remains unclear. PURPOSE: The purpose of this study was to assess the clinicopathological and prognostic significance of AIF1L expression levels and biological function in breast cancer. PATIENTS AND

methodsWe used immunohistochemistry to detect the expression of AIF1L in breast cancer. We also analyzed the expression of AIF1L in breast cancer using the Cancer Genome Atlas (TCGA) cohort and the Cancer Cell Line Encyclopedia (CCLE). Furthermore, both in vitro assays were used to determine the effect of AIF1L on malignant behavior in breast cancer cells.

resultsWe detected AIF1L expression in tissue microarrays through immunohistochemistry and found that protein expression was significantly lower in BC tissues (28.6%, 82/287) compared to tumor-adjacent tissues (58.3%, 28/48) (

conclusionThese findings suggest that AIF1L is a potential prognostic biomarker that plays a vital role in regulating the cytoskeleton in breast cancer.

Indexed as

AIF1Lbreast cancercytoskeletonTCGA

Identifiers

PMID30233209
PMCPMC6134948
OpenAlexW2889987549

What OpenQuestion holds

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Registered trials

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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.