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An anoikis-related lncRNA signature is a useful tool for predicting the prognosis of patients with lung adenocarcinoma

BACKGROUND: Anoikis-related long non-coding RNAs (ARLs) play a critical role in tumor metastasis and progression, suggesting that they may serve as risk markers for cancer. This study aimed to investigate the prognostic value of ARLs in patients with lung adenocarcinoma (LUAD). METHODS: Clinical dat...

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Autores principales: Jiang, Xin, Gao, Yu-lu, Li, Jia-yan, Tong, Ying-ying, Meng, Zhao-yang, Yang, Shi-gui, Zhu, Chang-tai
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10694177/
http://dx.doi.org/10.1016/j.heliyon.2023.e22200
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author Jiang, Xin
Gao, Yu-lu
Li, Jia-yan
Tong, Ying-ying
Meng, Zhao-yang
Yang, Shi-gui
Zhu, Chang-tai
author_facet Jiang, Xin
Gao, Yu-lu
Li, Jia-yan
Tong, Ying-ying
Meng, Zhao-yang
Yang, Shi-gui
Zhu, Chang-tai
author_sort Jiang, Xin
collection PubMed
description BACKGROUND: Anoikis-related long non-coding RNAs (ARLs) play a critical role in tumor metastasis and progression, suggesting that they may serve as risk markers for cancer. This study aimed to investigate the prognostic value of ARLs in patients with lung adenocarcinoma (LUAD). METHODS: Clinical data, RNA sequencing (RNA-seq) data, and mutation data from the LUAD project were obtained from The Cancer Genome Atlas (TCGA) database. The Molecular Signatures Database (MSigDB) and the GeneCard database were used to collect an anoikis-related gene (ARG) set. Pearson correlation analysis was performed to identify ARLs. LASSO and Cox regression were then used to establish a prognostic risk signature for ARLs. The median risk score served as the basis for categorizing patients into high and low-risk groups. Kaplan-Meier analysis was utilized to compare the prognosis between these two groups. The study also examined the associations between risk scores and prognosis, clinicopathological characteristics, immune status, tumor mutation burden (TMB), and chemotherapeutic agents. LncRNA expression was assessed using quantitative real-time PCR (qRT-PCR). RESULTS: A total of 480 RNA expression profiles, 501 ARGs, and 2698 ARLs were obtained from the database. A prognostic ARL signature for LUAD was established, consisting of 9 lncRNAs. Patients in the low-risk group exhibited significantly better prognosis compared to those in the high-risk group (P < 0.001). The 9 lncRNAs from the ARL signature were identified as independent prognostic factors (P < 0.001). The signature demonstrated high accuracy in predicting LUAD prognosis, with area under the curve values exceeding 0.7. The risk scores for ARLs showed strong negative correlations with stroma score (P = 5.9E-07, R = −0.23), immune score (P = 9.7E-09, R = −0.26), and microenvironment score (P = 8E-11, R = −0.29). Additionally, the low-risk group exhibited significantly higher TMB compared to the high-risk group (P = 4.6E-05). High-risk status was significantly associated with lower half-maximal inhibitory concentrations for most chemotherapeutic drugs. CONCLUSION: This newly constructed signature based on nine ARLs is a useful instrument for the risk stratification of LUAD patients. The signature has potential clinical significance for predicting the prognosis of LUAD patients and guiding personalized immunotherapy.
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spelling pubmed-106941772023-12-05 An anoikis-related lncRNA signature is a useful tool for predicting the prognosis of patients with lung adenocarcinoma Jiang, Xin Gao, Yu-lu Li, Jia-yan Tong, Ying-ying Meng, Zhao-yang Yang, Shi-gui Zhu, Chang-tai Heliyon Research Article BACKGROUND: Anoikis-related long non-coding RNAs (ARLs) play a critical role in tumor metastasis and progression, suggesting that they may serve as risk markers for cancer. This study aimed to investigate the prognostic value of ARLs in patients with lung adenocarcinoma (LUAD). METHODS: Clinical data, RNA sequencing (RNA-seq) data, and mutation data from the LUAD project were obtained from The Cancer Genome Atlas (TCGA) database. The Molecular Signatures Database (MSigDB) and the GeneCard database were used to collect an anoikis-related gene (ARG) set. Pearson correlation analysis was performed to identify ARLs. LASSO and Cox regression were then used to establish a prognostic risk signature for ARLs. The median risk score served as the basis for categorizing patients into high and low-risk groups. Kaplan-Meier analysis was utilized to compare the prognosis between these two groups. The study also examined the associations between risk scores and prognosis, clinicopathological characteristics, immune status, tumor mutation burden (TMB), and chemotherapeutic agents. LncRNA expression was assessed using quantitative real-time PCR (qRT-PCR). RESULTS: A total of 480 RNA expression profiles, 501 ARGs, and 2698 ARLs were obtained from the database. A prognostic ARL signature for LUAD was established, consisting of 9 lncRNAs. Patients in the low-risk group exhibited significantly better prognosis compared to those in the high-risk group (P < 0.001). The 9 lncRNAs from the ARL signature were identified as independent prognostic factors (P < 0.001). The signature demonstrated high accuracy in predicting LUAD prognosis, with area under the curve values exceeding 0.7. The risk scores for ARLs showed strong negative correlations with stroma score (P = 5.9E-07, R = −0.23), immune score (P = 9.7E-09, R = −0.26), and microenvironment score (P = 8E-11, R = −0.29). Additionally, the low-risk group exhibited significantly higher TMB compared to the high-risk group (P = 4.6E-05). High-risk status was significantly associated with lower half-maximal inhibitory concentrations for most chemotherapeutic drugs. CONCLUSION: This newly constructed signature based on nine ARLs is a useful instrument for the risk stratification of LUAD patients. The signature has potential clinical significance for predicting the prognosis of LUAD patients and guiding personalized immunotherapy. Elsevier 2023-11-11 /pmc/articles/PMC10694177/ http://dx.doi.org/10.1016/j.heliyon.2023.e22200 Text en © 2023 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Research Article
Jiang, Xin
Gao, Yu-lu
Li, Jia-yan
Tong, Ying-ying
Meng, Zhao-yang
Yang, Shi-gui
Zhu, Chang-tai
An anoikis-related lncRNA signature is a useful tool for predicting the prognosis of patients with lung adenocarcinoma
title An anoikis-related lncRNA signature is a useful tool for predicting the prognosis of patients with lung adenocarcinoma
title_full An anoikis-related lncRNA signature is a useful tool for predicting the prognosis of patients with lung adenocarcinoma
title_fullStr An anoikis-related lncRNA signature is a useful tool for predicting the prognosis of patients with lung adenocarcinoma
title_full_unstemmed An anoikis-related lncRNA signature is a useful tool for predicting the prognosis of patients with lung adenocarcinoma
title_short An anoikis-related lncRNA signature is a useful tool for predicting the prognosis of patients with lung adenocarcinoma
title_sort anoikis-related lncrna signature is a useful tool for predicting the prognosis of patients with lung adenocarcinoma
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10694177/
http://dx.doi.org/10.1016/j.heliyon.2023.e22200
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