Evidence map›Paper›PMID 36505295›Full record

ArticleAmerican journal of translational research2022

Identification of candidate miRNA biomarkers correlated with the prognosis of cell carcinoma and endocervical adenocarcinoma via integrated bioinformatics analysis.

Shuang Zhi, Bengui Jiang, Wenying Yu, Yan Li, Hanjin Wang, Teng Zhou, Nan Li

Abstract read
In one paragraph

Article in American journal of translational research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

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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

1 citing paper in PubMed.

  1. 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

7 authors.

Shuang ZhiFour Gynecological Wards, Ningbo Women & Children's Hospital No. 339 Liuting Street, Haishu District, Ningbo 315000, Zhejiang Province, China.
Bengui JiangFour Gynecological Wards, Ningbo Women & Children's Hospital No. 339 Liuting Street, Haishu District, Ningbo 315000, Zhejiang Province, China.
Wenying YuDiagnostic Pathology Center, Ningbo Diagnostic Pathology Center No. 685, Huancheng North Road East, Jiangbei District, Ningbo 315021, Zhejiang Province, China.
Yan LiFour Gynecological Wards, Ningbo Women & Children's Hospital No. 339 Liuting Street, Haishu District, Ningbo 315000, Zhejiang Province, China.
Hanjin WangFour Gynecological Wards, Ningbo Women & Children's Hospital No. 339 Liuting Street, Haishu District, Ningbo 315000, Zhejiang Province, China.
Teng ZhouFour Gynecological Wards, Ningbo Women & Children's Hospital No. 339 Liuting Street, Haishu District, Ningbo 315000, Zhejiang Province, China.
Nan LiFour Gynecological Wards, Ningbo Women & Children's Hospital No. 339 Liuting Street, Haishu District, Ningbo 315000, Zhejiang Province, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesThis study was designed to explore MicroRNAs (miRNAs) associated with the prognosis of cell carcinoma and endocervical adenocarcinoma (CESC) to search for biomarkers of CESC and provide guidelines for the clinical treatment.

methodsmRNAs of CESC patients were downloaded from The Cancer Genome Atlas (TCGA), and miRNA expression and clinical data of the patients were preprocessed. Key miRNAs associated with the prognosis of cervical cancer were identified by weighted gene co-expression network (WGCNA). The corresponding target genes were intersected with differentially expressed genes (DEGs) acquired from variation analysis, and the pathways and functional enrichment of genes were analyzed. Key genes were screened by Kaplan-Meier (K-M) survival analysis. Risk models were constructed using Cox proportional hazard regression model and the Least Absolute Shrinkage and Selection Operator (LASSO) method, and the predictive value of the models was evaluated by time-associated receiver operating characteristic (ROC) curves. Finally, independent prognostic factors were identified by COX analysis.

resultsThe hsa-miR-3150b-3p associated with the prognosis of CESC was identified by WGCNA. A total of 136 target genes were differentially expressed in CESC tissue and were associated with biological processes such as phylogeny, multicellular organism development and cell development. CBX7, ENPEP, FAIM2, IGF1, NUP62CL and TSC22D3 were associated with the prognosis of CESC, and a prognostic prediction model was constructed using these six genes, which had a good predictive value for the prognosis of cervical cancer within 1, 3 and 5 years (AUC: 0.784, 0.680 and 0.683, respectively). Among them, ENPEP (hazard ratio = 1.3996, 95% confidence interval: 1.0552-1.8565) was identified as an independent prognostic factor.

conclusionsIn this study, a highly accurate prognostic model consisting of six gene signatures was developed to predict the prognosis of patients with cervical cancer, which provides a reference for developing individualized treatment plans for patients.

Indexed as

Cell carcinoma and endocervical adenocarcinomamiRNAprognosisrisk modeltarget gene

Identifiers

PMID36505295
PMCPMC9730082

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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 Socratic graph.