Evidence map›Paper›PMID 35031063›Full record

ArticleJournal of ovarian research2022

A prognostic model based on immune-related long noncoding RNAs for patients with epithelial ovarian cancer.

Yao Peng, Hui Wang, Qi Huang, Jingjing Wu, Mingjun Zhang

Open access · goldAbstract read
In one paragraph

Article in Journal of ovarian research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 pooled it
1.4field-weighted citation impact, top 19% 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

14 citing papers in PubMed, 1 synthesis or guideline pooled it, 17 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Establishment of a Prognostic Necroptosis-Related lncRNA Signature in Ovarian Cancer.Combinatorial chemistry & high throughput screening · 2026
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  5. Cells · 2024
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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

5 authors at 2 institutions in 1 country.

Yao PengDepartment of Oncology, The Second Affiliated Hospital of Anhui Medical University, No. 678, Furong Road, Hefei, 230601, Anhui, P.R. China.
Hui WangDepartment of Oncology, Lu'an People's Hospital of Anhui Province, No. 21, West Anhui Road, Lu'an, 237006, Anhui, P.R. China.
Qi HuangDepartment of Oncology, The Second Affiliated Hospital of Anhui Medical University, No. 678, Furong Road, Hefei, 230601, Anhui, P.R. China.
Jingjing WuDepartment of Oncology, The Second Affiliated Hospital of Anhui Medical University, No. 678, Furong Road, Hefei, 230601, Anhui, P.R. China.
Mingjun ZhangDepartment of Oncology, The Second Affiliated Hospital of Anhui Medical University, No. 678, Furong Road, Hefei, 230601, Anhui, P.R. China. zhangmjayd@126.com.ORCID http://orcid.org/0000-0001-5212-9322
Anhui Medical University · CNLu'an First People's Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundLong noncoding RNAs (lncRNAs) are important regulators of gene expression and can affect a variety of physiological processes. Recent studies have shown that immune-related lncRNAs play an important role in the tumour immune microenvironment and may have potential application value in the treatment and prognosis prediction of tumour patients. Epithelial ovarian cancer (EOC) is characterized by a high incidence and poor prognosis. However, there are few studies on immune-related lncRNAs in EOC. In this study, we focused on immune-related lncRNAs associated with survival in EOC.

methodsWe downloaded mRNA data for EOC patients from The Cancer Genome Atlas (TCGA) database and mRNA data for normal ovarian tissue from the Genotype-Tissue Expression (GTEx) database and identified differentially expressed genes through differential expression analysis. Immune-related lncRNAs were obtained through intersection and coexpression analysis of differential genes and immune-related genes from the Immunology Database and Analysis Portal (ImmPort). Samples in the TCGA EOC cohort were randomly divided into a training set, validation set and combination set. In the training set, Cox regression analysis and LASSO regression were performed to construct an immune-related lncRNA signature. Kaplan-Meier survival analysis, time-dependent ROC curve analysis, Cox regression analysis and principal component analysis were performed for verification in the training set, validation set and combination set. Further studies of pathways and immune cell infiltration were conducted through Gene Set Enrichment Analysis (GSEA) and the Timer data portal.

resultsAn immune-related lncRNA signature was identified in EOC, which was composed of six immune-related lncRNAs (KRT7-AS, USP30-AS1, AC011445.1, AP005205.2, DNM3OS and AC027348.1). The signature was used to divide patients into high-risk and low-risk groups. The overall survival of the high-risk group was lower than that of the low-risk group and was verified to be robust in both the validation set and the combination set. The signature was confirmed to be an independent prognostic biomarker. Principal component analysis showed the different distribution patterns of high-risk and low-risk groups. This signature may be related to immune cell infiltration (mainly macrophages) and differential expression of immune checkpoint-related molecules (PD-1, PDL1, etc.).

conclusionsWe identified and established a prognostic signature of immune-related lncRNAs in EOC, which will be of great value in predicting the prognosis of clinical patients and may provide a new perspective for immunological research and individualized treatment in EOC.

Indexed as

Biomarkers, TumorCarcinoma, Ovarian EpithelialDatabases, GeneticFemaleGene Expression Regulation, NeoplasticHumansImmune Checkpoint ProteinsKaplan-Meier EstimateNomogramsOvarian NeoplasmsPrognosisRisk FactorsRNA, Long NoncodingROC CurveSurvival RateTumor MicroenvironmentBiomarkers, TumorImmune Checkpoint ProteinsRNA, Long NoncodingEpithelial ovarian cancerImmuneLong noncoding RNAsPrognostic signatureTCGA

Identifiers

PMID35031063
PMCPMC8760785
OpenAlexW4221024299

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.