Evidence map›Paper›PMID 32021278›Full record

ArticleOncoTargets and therapy2020

Transcriptome Analysis Reveals Key Genes and Pathways Associated with Metastasis in Breast Cancer.

Wei Li, Jianling Liu, Bin Zhang, Qingli Bie, Hui Qian, Wenrong Xu

Open access · goldAbstract read
In one paragraph

Article in OncoTargets and therapy, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
1.7field-weighted citation impact, top 16% 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

17 citing papers in PubMed, 28 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

6 authors at 3 institutions in 1 country.

Wei Li *Key Laboratory of Laboratory Medicine of Jiangsu Province, School of Medicine, Jiangsu University, Zhenjiang, Jiangsu, People's Republic of China.ORCID 0000-0002-3842-5165
Jianling Liu *Central Lab, The First Affiliated Hospital of Hebei North University, Zhangjiakou, Hebei, People's Republic of China.
Bin ZhangDepartment of Laboratory Medicine, Affiliated Hospital of Jining Medical University, Jining, Shandong, People's Republic of China.
Qingli BieDepartment of Laboratory Medicine, Affiliated Hospital of Jining Medical University, Jining, Shandong, People's Republic of China.
Hui QianKey Laboratory of Laboratory Medicine of Jiangsu Province, School of Medicine, Jiangsu University, Zhenjiang, Jiangsu, People's Republic of China.
Wenrong XuKey Laboratory of Laboratory Medicine of Jiangsu Province, School of Medicine, Jiangsu University, Zhenjiang, Jiangsu, People's Republic of China.
Jiangsu University · CNAffiliated Hospital of Jining Medical University · CNHebei North University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMetastasis is the major cause of death in breast cancer patients. Although the strategies targeting metastasis have promoted survival, the underlying mechanisms still remain unclear. In this study, we used microarray data of primary breast tumor, tumor derived from bone and liver, and skin metastatic tissue, to identify the key genes and pathways that are involved in metastasis in breast cancer.

methodsWe first calculated the differentially expressed genes (DEGs) between three metastatic tissues and primary tumor tissue, and then used it to perform Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. Further, we analyzed the correlation of genes enriched in GO terms and KEGG pathways with survival of breast cancer patients. To identify the key genes and pathways associated with metastasis, we overlapped the DEGs and KEGG pathways. In our in vitro experiments, we knocked down the key gene,

resultsWe identified six genes (

conclusionOur results reveal the key genes and signaling pathways that contribute to metastasis, and highlight that strategic targeting of

Indexed as

breast cancerkey genesmetastasissignaling pathwaystranscriptome microarray data

Identifiers

PMID32021278
PMCPMC6968804
OpenAlexW2998824145

What OpenQuestion holds

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LicenceCC BY-NC
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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.