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Article: Genome instability-derived genes as a novel prognostic signature for lung adenocarcinoma

TitleGenome instability-derived genes as a novel prognostic signature for lung adenocarcinoma
Authors
Keywordscopy number variation
fusion genes
genome instability
lung adenocarcinoma
overall survival prediction
somatic mutations
Issue Date16-Aug-2023
PublisherFrontiers Media
Citation
Frontiers in Cell and Developmental Biology, 2023, v. 11 How to Cite?
Abstract

Background: An increasing number of patients are being diagnosed with lung adenocarcinoma, but there remains limited progress in enhancing prognostic outcomes and improving survival rates for these patients. Genome instability is considered a contributing factor, as it enables other hallmarks of cancer to acquire functional capabilities, thus allowing cancer cells to survive, proliferate, and disseminate. Despite the importance of genome instability in cancer development, few studies have explored the prognostic signature associated with genome instability for lung adenocarcinoma.Methods: In the study, we randomly divided 397 lung adenocarcinoma patients from The Cancer Genome Atlas database into a training group (n = 199) and a testing group (n = 198). By calculating the cumulative counts of genomic alterations for each patient in the training group, we distinguished the top 25% and bottom 25% of patients. We then compared their gene expressions to identify genome instability-related genes. Next, we used univariate and multivariate Cox regression analyses to identify the prognostic signature. We also performed the Kaplan-Meier survival analysis and the log-rank test to evaluate the performance of the identified prognostic signature. The performance of the signature was further validated in the testing group, in The Cancer Genome Atlas dataset, and in external datasets. We also conducted a time-dependent receiver operating characteristic analysis to compare our signature with established prognostic signatures to demonstrate its potential clinical value.Results: We identified GULPsig, which includes IGF2BP1, IGF2BP3, SMC1B, CLDN6, and LY6K, as a prognostic signature for lung adenocarcinoma patients from 42 genome instability-related genes. Based on the risk score of the risk model with GULPsig, we successfully stratified the patients into high- and low-risk groups according to the results of the Kaplan-Meier survival analysis and the log-rank test. We further validated the performance of GULPsig as an independent prognostic signature and observed that it outperformed established prognostic signatures.Conclusion: We provided new insights to explore the clinical application of genome instability and identified GULPsig as a potential prognostic signature for lung adenocarcinoma patients.


Persistent Identifierhttp://hdl.handle.net/10722/339153
ISSN
2023 Impact Factor: 4.6
2023 SCImago Journal Rankings: 1.576
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorZhang, X-
dc.contributor.authorLam, TW-
dc.contributor.authorTing, HF-
dc.date.accessioned2024-03-11T10:34:18Z-
dc.date.available2024-03-11T10:34:18Z-
dc.date.issued2023-08-16-
dc.identifier.citationFrontiers in Cell and Developmental Biology, 2023, v. 11-
dc.identifier.issn2296-634X-
dc.identifier.urihttp://hdl.handle.net/10722/339153-
dc.description.abstract<p>Background: An increasing number of patients are being diagnosed with lung adenocarcinoma, but there remains limited progress in enhancing prognostic outcomes and improving survival rates for these patients. Genome instability is considered a contributing factor, as it enables other hallmarks of cancer to acquire functional capabilities, thus allowing cancer cells to survive, proliferate, and disseminate. Despite the importance of genome instability in cancer development, few studies have explored the prognostic signature associated with genome instability for lung adenocarcinoma.Methods: In the study, we randomly divided 397 lung adenocarcinoma patients from The Cancer Genome Atlas database into a training group (n = 199) and a testing group (n = 198). By calculating the cumulative counts of genomic alterations for each patient in the training group, we distinguished the top 25% and bottom 25% of patients. We then compared their gene expressions to identify genome instability-related genes. Next, we used univariate and multivariate Cox regression analyses to identify the prognostic signature. We also performed the Kaplan-Meier survival analysis and the log-rank test to evaluate the performance of the identified prognostic signature. The performance of the signature was further validated in the testing group, in The Cancer Genome Atlas dataset, and in external datasets. We also conducted a time-dependent receiver operating characteristic analysis to compare our signature with established prognostic signatures to demonstrate its potential clinical value.Results: We identified GULPsig, which includes IGF2BP1, IGF2BP3, SMC1B, CLDN6, and LY6K, as a prognostic signature for lung adenocarcinoma patients from 42 genome instability-related genes. Based on the risk score of the risk model with GULPsig, we successfully stratified the patients into high- and low-risk groups according to the results of the Kaplan-Meier survival analysis and the log-rank test. We further validated the performance of GULPsig as an independent prognostic signature and observed that it outperformed established prognostic signatures.Conclusion: We provided new insights to explore the clinical application of genome instability and identified GULPsig as a potential prognostic signature for lung adenocarcinoma patients.</p>-
dc.languageeng-
dc.publisherFrontiers Media-
dc.relation.ispartofFrontiers in Cell and Developmental Biology-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.subjectcopy number variation-
dc.subjectfusion genes-
dc.subjectgenome instability-
dc.subjectlung adenocarcinoma-
dc.subjectoverall survival prediction-
dc.subjectsomatic mutations-
dc.titleGenome instability-derived genes as a novel prognostic signature for lung adenocarcinoma-
dc.typeArticle-
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.3389/fcell.2023.1224069-
dc.identifier.pmid37655157-
dc.identifier.scopuseid_2-s2.0-85169663023-
dc.identifier.volume11-
dc.identifier.eissn2296-634X-
dc.identifier.isiWOS:001058008600001-
dc.publisher.placeLAUSANNE-
dc.identifier.issnl2296-634X-

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