Evidence map›Paper›PMID 31432147›Full record

ArticleMolecular medicine reports2019

An 8‑gene signature predicts the prognosis of cervical cancer following radiotherapy.

Fei Xie, Dan Dong, Na Du, Liang Guo, Weihua Ni, Hongyan Yuan, Nannan Zhang, Jiang Jie, Guomu Liu, Guixiang Tai

Abstract readValidation Study
In one paragraph

Article in Molecular medicine reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 pooled it
–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

9 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Radiotherapy resistance: identifying universal biomarkers for various human cancers.Journal of cancer research and clinical oncology · 2022
    Review
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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

10 authors.

Fei XieDepartment of Immunology, College of Basic Medical Science, Jilin University, Changchun, Jilin 130021, P.R. China.
Dan DongDepartment of Obstetrics and Gynecology, The First Hospital of Jilin University, Changchun, Jilin 130021, P.R. China.
Na DuDepartment of Infections, The First Hospital of Jilin University, Changchun, Jilin 130021, P.R. China.
Liang GuoDepartment of Pathology, The First Hospital of Jilin University, Changchun, Jilin 130021, P.R. China.
Weihua NiDepartment of Immunology, College of Basic Medical Science, Jilin University, Changchun, Jilin 130021, P.R. China.
Hongyan YuanDepartment of Immunology, College of Basic Medical Science, Jilin University, Changchun, Jilin 130021, P.R. China.
Nannan ZhangDepartment of Immunology, College of Basic Medical Science, Jilin University, Changchun, Jilin 130021, P.R. China.
Jiang JieDepartment of Immunology, College of Basic Medical Science, Jilin University, Changchun, Jilin 130021, P.R. China.
Guomu LiuDepartment of Nephrology, The First Hospital of Jilin University, Changchun, Jilin 130021, P.R. China.
Guixiang TaiDepartment of Immunology, College of Basic Medical Science, Jilin University, Changchun, Jilin 130021, P.R. China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Gene expression and DNA methylation levels affect the outcomes of patients with cancer. The present study aimed to establish a multigene risk model for predicting the outcomes of patients with cervical cancer (CerC) treated with or without radiotherapy. RNA sequencing training data with matched DNA methylation profiles were downloaded from The Cancer Genome Atlas database. Patients were divided into radiotherapy and non‑radiotherapy groups according to the treatment strategy. Differently expressed and methylated genes between the two groups were identified, and 8 prognostic genes were identified using Cox regression analysis. The optimized risk model based on the 8‑gene signature was defined using the Cox's proportional hazards model. Kaplan‑Meier survival analysis indicated that patients with higher risk scores exhibited poorer survival compared with patients with lower risk scores (log‑rank test, P=3.22x10‑7). Validation using the GSE44001 gene set demonstrated that patients in the high‑risk group exhibited a shorter survival time comprared with the low‑risk group (log‑rank test, P=3.01x10‑3). The area under the receiver operating characteristic curve values for the training and validation sets were 0.951 and 0.929, respectively. Cox regression analyses indicated that recurrence and risk status were risk factors for poor outcomes in patients with CerC treated with or without radiotherapy. The present study defined that the 8‑gene signature was an independent risk factor for the prognosis of patients with CerC. The 8‑gene prognostic model had predictive power for CerC prognosis.

Indexed as

Gene Expression Regulation, NeoplasticModels, BiologicalUterine Cervical NeoplasmsAdultDisease-Free SurvivalFemaleHumansInterleukin-8Middle AgedNeoplasm ProteinsPredictive Value of TestsSurvival RateCXCL8 protein, humanInterleukin-8Neoplasm Proteins

Identifiers

PMID31432147
PMCPMC6755236

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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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 Socratic graph.