Evidence map›Paper›PMID 30271202›Full record

ArticleCancer management and research2018

Identification of key candidate genes and small molecule drugs in cervical cancer by bioinformatics strategy.

Xin Tang, Yicong Xu, Lin Lu, Yang Jiao, Jianjun Liu, Linlin Wang, Hongbo Zhao

Open access · goldAbstract read
In one paragraph

Article in Cancer management and research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 1 pooled it
3.0field-weighted citation impact, top 9% 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

15 citing papers in PubMed, 1 synthesis or guideline pooled it, 31 citations in OpenAlex.

  1. Prognostic and predictive values of CXCL10 in colorectal cancer.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2020
    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

7 authors at 1 institution in 1 country.

Xin TangSchool of Rehabilitation, Kunming Medical University, Kunming, China.
Yicong XuInstitute of Molecular and Clinical Medicine, Kunming Medical University, Kunming, China, zhao.hongbo@hotmail.com.
Lin LuInstitute of Molecular and Clinical Medicine, Kunming Medical University, Kunming, China, zhao.hongbo@hotmail.com.
Yang JiaoInstitute of Molecular and Clinical Medicine, Kunming Medical University, Kunming, China, zhao.hongbo@hotmail.com.
Jianjun LiuInstitute of Molecular and Clinical Medicine, Kunming Medical University, Kunming, China, zhao.hongbo@hotmail.com.
Linlin WangInstitute of Molecular and Clinical Medicine, Kunming Medical University, Kunming, China, zhao.hongbo@hotmail.com.
Hongbo ZhaoInstitute of Molecular and Clinical Medicine, Kunming Medical University, Kunming, China, zhao.hongbo@hotmail.com.
Kunming Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeCervical cancer (CC) is one of the most common malignant tumors among women. The present study aimed at integrating two expression profile datasets to identify critical genes and potential drugs in CC. MATERIALS AND

methodsExpression profiles, GSE7803 and GSE9750, were integrated using bioinformatics methods, including differentially expressed genes analysis, Kyoto Encyclopedia of Genes and Genomes pathway analysis, and protein-protein interaction (PPI) network construction. Subsequently, survival analysis was performed among the key genes using Gene Expression Profiling Interactive Analysis websites. Connectivity Map (CMap) was used to query potential drugs for CC.

resultsA total of 145 upregulated genes and 135 downregulated genes in CC were identified. The functional changes of these differentially expressed genes related to CC were mainly associated with cell cycle, DNA replication, p53 signaling pathway, and oocyte meiosis. A PPI network was identified by STRING with 220 nodes and 2,111 edges. Thirteen key genes were identified as the intersecting genes of the enrichment pathways and the top 20 nodes in PPI network. Survival analysis revealed that high mRNA expression of

conclusionOur study found key dysregulated genes involved in CC and potential drugs to combat it, which might provide insights into CC pathogenesis and might shed light on potential CC treatments.

Indexed as

bioinformaticsbiomarkercell cyclecervical cancerdrug

Identifiers

PMID30271202
PMCPMC6145638
OpenAlexW2890999161

What OpenQuestion holds

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LicenceCC BY-NC
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.