Evidence map›Paper›PMID 34734036›Full record

ArticleAnnals of translational medicine2021

A novel immune-related ceRNA network that predicts prognosis and immunotherapy response in lung adenocarcinoma.

Wei-Jing Gong, Tao Zhou, San-Lan Wu, Yi-Fei Huang, Li-Ping Xiang, Jia-Qiang Xu, Yong Han, Yong-Ning Lv, Fang Zeng, Yu Zhang

Open access · diamondAbstract read
In one paragraph

Article in Annals of translational medicine, 2021. 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
0.7field-weighted citation impact, top 37% 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

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

  1. miRNAs Related to Immune Checkpoint Inhibitor Response: A Systematic Review.International journal of molecular sciences · 2024
    Pooled it
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  7. A new prognostic model forJournal of thoracic disease · 2023
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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 at 2 institutions in 1 country.

Wei-Jing GongDepartment of Pharmacy, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Tao ZhouDepartment of Pharmacy, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
San-Lan WuDepartment of Pharmacy, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Yi-Fei HuangDepartment of Pharmacy, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Li-Ping XiangDepartment of Pharmacy, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Jia-Qiang XuDepartment of Pharmacy, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Yong HanDepartment of Pharmacy, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Yong-Ning LvDepartment of Pharmacy, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Fang ZengDepartment of Pharmacy, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Yu ZhangDepartment of Pharmacy, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Huazhong University of Science and Technology · CNUnion Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe tumor microenvironment plays an important role in the progression and malignancy of lung adenocarcinoma and affects the immunotherapy response. There is increasing evidence that long non-coding RNAs (lncRNAs) as competing endogenous RNAs (ceRNAs) have significant functions in the development and treatment response of various kinds of cancer. This study aimed to explore the association between immune-related lncRNA-microRNA (miRNA)-messenger RNA (mRNA)-ceRNA networks, and the prognosis of and immunotherapy response in lung adenocarcinoma.

methodsRNA-sequencing (RNA-seq) and miRNA-seq data from The Cancer Genome Atlas (TCGA) were used to evaluate the infiltration of immune cells in lung adenocarcinoma samples by undertaking a single-sample gene set enrichment analysis (ssGSEA) to divide the cells into high and low immune cell infiltration groups. The differentially expressed mRNA (DEmRNA) was further analyzed by a weighted gene co-expression network analysis (WGCNA), search tool for recurring instances of neighboring genes (STRING), and Cytoscape to select hub genes. The ceRNA network was constructed using Cytoscape. Additionally, survival analyses were conducted to screen out prognostic candidate genes.

resultsSeven thousand five hundred and thirty-eight mRNAs, 540 lncRNAs, and 138 miRNAs were found to be differentially expressed between the high and low immune cell infiltration groups. The two DEmRNA modules most significantly associated with immune cell infiltration were further analyzed, and four clusters, including 179 DEmRNAs, were selected based on Molecular Complex Detection (MCODE) scores. The selected DEmRNAs in the four clusters were mainly enriched in pathways involved in regulating the immune response. Ultimately, a ceRNA network of

conclusionsThe present study extends understandings of immune-related lncRNA-miRNA-mRNA-ceRNA networks and identifies novel targets and a regulatory pathway for anti-tumor immunotherapy.

Indexed as

Competing endogenous RNA network (ceRNA network)immune infiltrationlong non-coding RNA (lncRNA)lung adenocarcinomaprognosis

Identifiers

PMID34734036
PMCPMC8506752
OpenAlexW3202409399

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.