Evidence map›Paper›PMID 39372720›Full record

ArticlePeerJ2024

Identification of 10 differentially expressed genes involved in the tumorigenesis of cervical cancer

Jia Xu, Wen Yang, Xiufeng Xie, Chenglei Gu, Luyang Zhao, Feng Liu, Nina Zhang, Yuge Bai, Dan Liu, Hainan Liu and 2 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in PeerJ, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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

2 citing papers in PubMed.

  1. Article
  2. 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

12 authors.

Jia XuSchool of Medicine, Nankai University, Tianjin, China.
Wen YangDepartment of Obstetrics and Gynecology, The Seventh Medical Center of Chinese PLA General Hospital, Beijing, China.
Xiufeng XieDepartment of Obstetrics and Gynecology, The Seventh Medical Center of Chinese PLA General Hospital, Beijing, China.
Chenglei GuDepartment of Obstetrics and Gynecology, The Seventh Medical Center of Chinese PLA General Hospital, Beijing, China.
Luyang ZhaoDepartment of Obstetrics and Gynecology, The Seventh Medical Center of Chinese PLA General Hospital, Beijing, China.
Feng LiuDepartment of Obstetrics and Gynecology, The Seventh Medical Center of Chinese PLA General Hospital, Beijing, China.
Nina ZhangDepartment of Obstetrics and Gynecology, The Seventh Medical Center of Chinese PLA General Hospital, Beijing, China.
Yuge BaiDepartment of Obstetrics and Gynecology, The Seventh Medical Center of Chinese PLA General Hospital, Beijing, China.
Dan LiuDepartment of Obstetrics and Gynecology, The Seventh Medical Center of Chinese PLA General Hospital, Beijing, China.
Hainan LiuDepartment of Obstetrics and Gynecology, The Seventh Medical Center of Chinese PLA General Hospital, Beijing, China.
Xiangshu JinDepartment of Obstetrics and Gynecology, The Seventh Medical Center of Chinese PLA General Hospital, Beijing, China.
Yuanguang MengSchool of Medicine, Nankai University, Tianjin, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The incidence and mortality of cervical cancer remain high in female malignant tumors worldwide. There is still a lack of diagnostic and prognostic markers for cervical carcinoma. This study aimed to screen differentially expressed genes (DEGs) between normal and cervical cancer tissues to identify candidate genes for further research. Methods: Uterine cervical specimens were resected from our clinical patients after radical hysterectomy. Three patients' transcriptomic datasets were built by the next generation sequencing (NGS) results. DEGs were selected through the edgeR and DESeq2 packages in the R environment. Functional enrichment analysis, including GO/DisGeNET/KEGG/Reactome enrichment analysis, was performed. Normal and cervical cancer tissue data from the public databases TCGA and GTEx were collected to compare the expression levels of 10 selected DEGs in tumor and normal tissues. ROC curve and survival analysis were performed to compare the diagnostic and prognostic values of each gene. The expression levels of candidate genes were verified in 15 paired clinical specimens Results: There were 875 up-regulated and 1,482 down-regulated genes in cervical cancer samples compared with the paired adjacent normal cervical tissues according to the NGS analysis. The top 10 DEGs included Conclusions: In this study, we selected the top 10 DEGs which were down-regulated in cervical cancer tissues. All of them had dramatically diagnostic value.

Indexed as

CarcinogenesisGene Expression Regulation, NeoplasticHigh-Throughput Nucleotide SequencingUterine Cervical NeoplasmsBiomarkers, TumorFemaleGene Expression ProfilingHumansMiddle AgedPrognosisTranscriptomeBiomarkers, TumorCervical cancerDifferentially expressed genesNext-generation sequencingThe Cancer Genome Atlas

Identifiers

PMID39372720
PMCPMC11453159

What OpenQuestion holds

Textmetadata
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.