A nomogram based on A-to-I RNA editing predicting overall survival of patients with lung squamous carcinoma.


Journal

BMC cancer
ISSN: 1471-2407
Titre abrégé: BMC Cancer
Pays: England
ID NLM: 100967800

Informations de publication

Date de publication:
29 Jun 2022
Historique:
received: 06 05 2021
accepted: 10 06 2022
entrez: 29 6 2022
pubmed: 30 6 2022
medline: 2 7 2022
Statut: epublish

Résumé

Adenosine-to-inosine RNA editing (ATIRE) is characterized as non-mutational epigenetic reprogramming hallmark of cancer, while little is known about its predictive role in cancer survival. To explore survival-related ATIRE events in lung squamous cell carcinoma (LUSC), ATIRE profile, gene expression data, and corresponding clinical information of LUSC patients were downloaded from the TCGA database. Patients were randomly divided into a training (n = 134) and validation cohort (n = 94). Cox proportional hazards regression followed by least absolute shrinkage and selection operator algorithm were performed to identify survival-related ATIRE sites and to generate ATIRE risk score. Then a nomogram was constructed to predict overall survival (OS) of LUSC patients. The correlation of ATIRE level and host gene expression and ATIREs' effect on transcriptome expression were analyzed. Seven ATIRE sites that were TMEM120B chr12:122215052A > I, HMOX2 chr16:4533713A > I, CALCOCO2 chr17:46941503A > I, LONP2 chr16:48388244A > I, ZNF440 chr19:11945758A > I, CLCC1 chr1:109474650A > I, and CHMP3 chr2:86754288A > I were identified to generate the risk score, of which high levers were significantly associated with worse OS and progression-free survival in both the training and validation sets. High risk-score was also associated with advanced T stages and worse clinical stages. The nomogram performed well in predicting OS probability of LUSC. Moreover, the editing of ATIRE sites exerted a significant association with expression of host genes and affected several cancer-related pathways. This is the first comprehensive study to analyze the role of ATIRE events in predicting LUSC survival. The AITRE-based model might serve as a novel tool for LUSC survival prediction.

Sections du résumé

BACKGROUND BACKGROUND
Adenosine-to-inosine RNA editing (ATIRE) is characterized as non-mutational epigenetic reprogramming hallmark of cancer, while little is known about its predictive role in cancer survival.
METHODS METHODS
To explore survival-related ATIRE events in lung squamous cell carcinoma (LUSC), ATIRE profile, gene expression data, and corresponding clinical information of LUSC patients were downloaded from the TCGA database. Patients were randomly divided into a training (n = 134) and validation cohort (n = 94). Cox proportional hazards regression followed by least absolute shrinkage and selection operator algorithm were performed to identify survival-related ATIRE sites and to generate ATIRE risk score. Then a nomogram was constructed to predict overall survival (OS) of LUSC patients. The correlation of ATIRE level and host gene expression and ATIREs' effect on transcriptome expression were analyzed.
RESULTS RESULTS
Seven ATIRE sites that were TMEM120B chr12:122215052A > I, HMOX2 chr16:4533713A > I, CALCOCO2 chr17:46941503A > I, LONP2 chr16:48388244A > I, ZNF440 chr19:11945758A > I, CLCC1 chr1:109474650A > I, and CHMP3 chr2:86754288A > I were identified to generate the risk score, of which high levers were significantly associated with worse OS and progression-free survival in both the training and validation sets. High risk-score was also associated with advanced T stages and worse clinical stages. The nomogram performed well in predicting OS probability of LUSC. Moreover, the editing of ATIRE sites exerted a significant association with expression of host genes and affected several cancer-related pathways.
CONCLUSIONS CONCLUSIONS
This is the first comprehensive study to analyze the role of ATIRE events in predicting LUSC survival. The AITRE-based model might serve as a novel tool for LUSC survival prediction.

Identifiants

pubmed: 35768804
doi: 10.1186/s12885-022-09773-0
pii: 10.1186/s12885-022-09773-0
pmc: PMC9241197
doi:

Substances chimiques

Biomarkers, Tumor 0
CHMP3 protein, human 0
CLCC1 protein, human 0
Chloride Channels 0
Endosomal Sorting Complexes Required for Transport 0
RNA, Long Noncoding 0

Types de publication

Journal Article Randomized Controlled Trial

Langues

eng

Sous-ensembles de citation

IM

Pagination

715

Informations de copyright

© 2022. The Author(s).

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Auteurs

Li Liu (L)

The State Key Lab of Respiratory Disease, Institute of Public Health, Guangzhou Medical University, Xinzao, Panyu District, Guangzhou, 511436, China.

Jun Liu (J)

Department of Pulmonary and Critical Care Medicine, Guangzhou First People's Hospital, the Second Affiliated Hospital of South China University of Technology, Guangzhou, 510080, China.

Xiaoliang Deng (X)

The State Key Lab of Respiratory Disease, Institute of Public Health, Guangzhou Medical University, Xinzao, Panyu District, Guangzhou, 511436, China.

Li Tu (L)

Department of Respiratory Medicine, Hospital of Changan, Dongguan, 523843, China.

Zhuxiang Zhao (Z)

Department of Pulmonary and Critical Care Medicine, Guangzhou First People's Hospital, the Second Affiliated Hospital of South China University of Technology, Guangzhou, 510080, China.

Chenli Xie (C)

Department of Respiratory Medicine, Fifth People's Hospital of Dongguan, Dongguan, 523939, China.

Lei Yang (L)

The State Key Lab of Respiratory Disease, Institute of Public Health, Guangzhou Medical University, Xinzao, Panyu District, Guangzhou, 511436, China. leiyang@gzhmu.edu.cn.

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Classifications MeSH