Evidence map›Paper›PMID 33671013›Full record

ArticleInternational journal of molecular sciences2021

Immunogenomic Identification for Predicting the Prognosis of Cervical Cancer Patients.

Qun Wang, Aurelia Vattai, Theresa Vilsmaier, Till Kaltofen, Alexander Steger, Doris Mayr, Sven Mahner, Udo Jeschke, Helene Hildegard Heidegger

Open access · goldAbstract read
In one paragraph

Article in International journal of molecular sciences, 2021. 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
2.1field-weighted citation impact, top 12% 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, 26 citations in OpenAlex.

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  8. BMP6 inhibits gastric cancer growth and predicts good prognosis.Journal of gastrointestinal oncology · 2024
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  13. Analysis on tumor immune microenvironment and construction of a prognosis model for immune-related skin cutaneous melanoma.Zhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences · 2023
    Article
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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

9 authors at 3 institutions in 1 country.

Qun WangDepartment of Obstetrics and Gynecology, University Hospital, LMU Munich, 80377 Munich, Germany.
Aurelia VattaiDepartment of Obstetrics and Gynecology, University Hospital, LMU Munich, 80377 Munich, Germany.
Theresa VilsmaierDepartment of Obstetrics and Gynecology, University Hospital, LMU Munich, 80377 Munich, Germany.ORCID 0000-0003-0452-1148
Till KaltofenDepartment of Obstetrics and Gynecology, University Hospital, LMU Munich, 80377 Munich, Germany.ORCID 0000-0003-1137-211X
Alexander StegerKlinik für Innere Medizin I, Technische Universität München, 80333 Munich, Germany.ORCID 0000-0002-0033-6941
Doris MayrDepartment of Pathology, LMU Munich, 80377 Munich, Germany.
Sven MahnerDepartment of Obstetrics and Gynecology, University Hospital, LMU Munich, 80377 Munich, Germany.
Udo JeschkeDepartment of Obstetrics and Gynecology, University Hospital, LMU Munich, 80377 Munich, Germany.
Helene Hildegard HeideggerDepartment of Obstetrics and Gynecology, University Hospital, LMU Munich, 80377 Munich, Germany.
LMU Klinikum · DETechnical University of Munich · DEUniversity Hospital Augsburg · DE

Funding

China Scholarship Council Qun Wang
6 · The paper itself

Abstract

Cervical cancer is primarily caused by the infection of high-risk human papillomavirus (hrHPV). Moreover, tumor immune microenvironment plays a significant role in the tumorigenesis of cervical cancer. Therefore, it is necessary to comprehensively identify predictive biomarkers from immunogenomics associated with cervical cancer prognosis. The Cancer Genome Atlas (TCGA) public database has stored abundant sequencing or microarray data, and clinical data, offering a feasible and reliable approach for this study. In the present study, gene profile and clinical data were downloaded from TCGA, and the Immunology Database and Analysis Portal (ImmPort) database. Wilcoxon-test was used to compare the difference in gene expression. Univariate analysis was adopted to identify immune-related genes (IRGs) and transcription factors (TFs) correlated with survival. A prognostic prediction model was established by multivariate cox analysis. The regulatory network was constructed and visualized by correlation analysis and Cytoscape, respectively. Gene functional enrichment analysis was performed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). A total of 204 differentially expressed IRGs were identified, and 22 of them were significantly associated with the survival of cervical cancer. These 22 IRGs were actively involved in the JAK-STAT pathway. A prognostic model based on 10 IRGs (

Indexed as

AdenocarcinomaAgedBiomarkers, TumorCarcinoma, Squamous CellCase-Control StudiesFemaleFollow-Up StudiesGene Expression ProfilingGene Expression Regulation, NeoplasticHumansMiddle AgedPrognosisSurvival RateTumor MicroenvironmentUterine Cervical NeoplasmsBiomarkers, Tumorbioinformatics analysiscervical cancerKEGGTCGAtumor immune

Identifiers

PMID33671013
PMCPMC7957482
OpenAlexW3135842704

What OpenQuestion holds

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Registered trials

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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 OpenQuestion graph.