Evidence map›Paper›PMID 34306024›Full record

ArticleFrontiers in genetics2021

Identification and Validation of Immune-Related LncRNA Prognostic Signature for Lung Adenocarcinoma.

Guomin Wu, Qihao Wang, Ting Zhu, Linhai Fu, Zhupeng Li, Yuanlin Wu, Chu Zhang

Open access · goldAbstract read
In one paragraph

Article in Frontiers in genetics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed
2.2field-weighted citation impact, top 11% 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

27 citing papers in PubMed, 29 citations in OpenAlex.

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  8. LncRNA FAM30A Predicts Adverse Prognosis and Regulates Cellular Processes in Colorectal Cancer via Modulating miR-21-3p.The Turkish journal of gastroenterology : the official journal of Turkish Society of Gastroenterology · 2024
    Article
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  10. ChromogenicNon-coding RNA research · 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

7 authors at 2 institutions in 1 country.

Guomin WuSchool of Medicine, Shaoxing University, Shaoxing, China.
Qihao WangSchool of Medicine, Shaoxing University, Shaoxing, China.
Ting ZhuDepartment of Thoracic Surgery, Shaoxing People's Hospital, Shaoxing Hospital, Zhejiang University School of Medicine, Shaoxing, China.
Linhai FuDepartment of Thoracic Surgery, Shaoxing People's Hospital, Shaoxing Hospital, Zhejiang University School of Medicine, Shaoxing, China.
Zhupeng LiDepartment of Thoracic Surgery, Shaoxing People's Hospital, Shaoxing Hospital, Zhejiang University School of Medicine, Shaoxing, China.
Yuanlin WuDepartment of Thoracic Surgery, Shaoxing People's Hospital, Shaoxing Hospital, Zhejiang University School of Medicine, Shaoxing, China.
Chu ZhangDepartment of Thoracic Surgery, The First Affiliated Hospital of Shaoxing University (Shaoxing People's Hospital), Shaoxing, China.
Shaoxing People's Hospital · CNShaoxing University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study aimed to establish a prognostic risk model for lung adenocarcinoma (LUAD). We firstly divided 535 LUAD samples in TCGA-LUAD into high-, medium-, and low-immune infiltration groups by consensus clustering analysis according to immunological competence assessment by single-sample gene set enrichment analysis (ssGSEA). Profile of long non-coding RNAs (lncRNAs) in normal samples and LUAD samples in TCGA was used for a differential expression analysis in the high- and low-immune infiltration groups. A total of 1,570 immune-related differential lncRNAs in LUAD were obtained by intersecting the above results. Afterward, univariate COX regression analysis and multivariate stepwise COX regression analysis were conducted to screen prognosis-related lncRNAs, and an eight-immune-related-lncRNA prognostic signature was finally acquired (AL365181.2, AC012213.4, DRAIC, MRGPRG-AS1, AP002478.1, AC092168.2, FAM30A, and LINC02412). Kaplan-Meier analysis and ROC analysis indicated that the eight-lncRNA-based model was accurate to predict the prognosis of LUAD patients. Simultaneously, univariate COX regression analysis and multivariate COX regression analysis were undertaken on clinical features and risk scores. It was illustrated that the risk score was a prognostic factor independent from clinical features. Moreover, immune data of LUAD in the TIMER database were analyzed. The eight-immune-related-lncRNA prognostic signature was related to the infiltration of B cells, CD4+ T cells, and dendritic cells. GSEA enrichment analysis revealed significant differences in high- and low-risk groups in pathways like pentose phosphate pathway, ubiquitin mediated proteolysis, and P53 signaling pathway. This study helps to treat LUAD patients and explore molecules related to LUAD immune infiltration to deeply understand the specific mechanism.

Indexed as

immune infiltrationlncRNAlung adenocarcinomaprognosisrisk score

Identifiers

PMID34306024
PMCPMC8301374
OpenAlexW3179168983

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.