Evidence map›Paper›PMID 37065578›Full record

ArticleJournal of thoracic disease2023

Tumor necrosis factor-related lncRNAs predict prognosis and immunotherapy response for patients with lung adenocarcinoma.

Jin-Hua Chen, Xuan Wu, Zi-Ming Wang, Zi-Yang Liu, Bao-Xia He, Wen-Ping Song, Wen-Zhou Zhang

Open access · diamondAbstract read
In one paragraph

Article in Journal of thoracic disease, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.7field-weighted citation impact, top 25% 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

1 citing paper in PubMed, 3 citations in OpenAlex.

  1. Article
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 3 institutions in 1 country.

Jin-Hua Chen *Department of Pharmacy, Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Henan Engineering Research Center for Tumor Precision Medicine and Comprehensive Evaluation, Henan Provincial Key Laboratory of Anticancer Drug Research, Zhengzhou, China.
Xuan Wu *Department of Respiratory and Critical Care Medicine, Zhengzhou University People's Hospital, Zhengzhou, China.
Zi-Ming WangSchool of Medical Sciences, Henan University, Kaifeng, China.
Zi-Yang LiuDepartment of Respiratory and Critical Care Medicine, Zhengzhou University People's Hospital, Zhengzhou, China.
Bao-Xia HeDepartment of Pharmacy, Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Henan Engineering Research Center for Tumor Precision Medicine and Comprehensive Evaluation, Henan Provincial Key Laboratory of Anticancer Drug Research, Zhengzhou, China.
Wen-Ping SongDepartment of Pharmacy, Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Henan Engineering Research Center for Tumor Precision Medicine and Comprehensive Evaluation, Henan Provincial Key Laboratory of Anticancer Drug Research, Zhengzhou, China.
Wen-Zhou ZhangDepartment of Pharmacy, Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Henan Engineering Research Center for Tumor Precision Medicine and Comprehensive Evaluation, Henan Provincial Key Laboratory of Anticancer Drug Research, Zhengzhou, China.
Henan Cancer Hospital · CNZhengzhou University · CNHenan University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Lung adenocarcinoma (LUAD) has become one of the most lethal cancers, for which the recurrence and survival rates remain unfavorable. The tumor necrosis factor (TNF) family is involved in tumorigenesis and tumor progression. Various long non-coding RNAs (lncRNAs) play important roles by mediating the TNF family in cancer. Therefore, this study aimed to construct a TNF-related lncRNA signature to predict prognosis and immunotherapy response in LUAD. Methods: The expression of TNF family members and their related lncRNAs in a total of 500 enrolled LUAD patients was collected from The Cancer Genome Atlas (TCGA). Univariate Cox and the least absolute shrinkage and selection operator (LASSO)-Cox analysis was used to construct a TNF family-related lncRNA prognostic signature. Kaplan-Meier (KM) survival analysis was used to evaluate survival status. The time-dependent area under the receiver operating characteristic (ROC) curve (AUC) values were used to assess the predictive value of the signature to 1-, 2-, and 3-year overall survival (OS). Gene Ontology (GO) functional annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were applied to identify the signature-related biological pathways. Furthermore, tumor immune dysfunction and exclusion (TIDE) analysis was employed to evaluate immunotherapy response. Results: A total of 8 TNF-related lncRNAs significantly associated with OS of LUAD patients were used to construct a TNF family-related lncRNA prognostic signature. According to risk score, these patients were divided into high- and low-risk subgroups. The KM survival analysis indicated that patients in the high-risk group showed significantly less favorable OS than that of low-risk group. The AUC values in predicting 1-, 2-, and 3-year OS were 0.740, 0.738, and 0.758, respectively. Moreover, the GO and KEGG pathway analyses demonstrated that these lncRNAs were closely involved in immune-related signaling pathways. The further TIDE analysis indicated that high-risk patients had a lower TIDE score than that of low-risk patients, indicating that high-risk patients may be appropriate candidates for immunotherapy. Conclusions: For the first time, this study constructed and validated a prognostic predictive signature of LUAD patients based on TNF-related lncRNAs, and the signature showed good performance to predict immunotherapy response. Therefore, this signature may provide new strategies for individualized treatment of LUAD patients.

Indexed as

immunotherapy responselong non-coding RNAs (lncRNAs)Lung adenocarcinoma (LUAD)prognosistumor necrosis factor (TNF)

Identifiers

PMID37065578
PMCPMC10089852
OpenAlexW4360989870

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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.