Cargando…
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...
Autores principales: | , , , , , , |
---|---|
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 |
_version_ | 1785153316571840512 |
---|---|
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. |
format | Online Article Text |
id | pubmed-10694177 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT jiangxin ananoikisrelatedlncrnasignatureisausefultoolforpredictingtheprognosisofpatientswithlungadenocarcinoma AT gaoyulu ananoikisrelatedlncrnasignatureisausefultoolforpredictingtheprognosisofpatientswithlungadenocarcinoma AT lijiayan ananoikisrelatedlncrnasignatureisausefultoolforpredictingtheprognosisofpatientswithlungadenocarcinoma AT tongyingying ananoikisrelatedlncrnasignatureisausefultoolforpredictingtheprognosisofpatientswithlungadenocarcinoma AT mengzhaoyang ananoikisrelatedlncrnasignatureisausefultoolforpredictingtheprognosisofpatientswithlungadenocarcinoma AT yangshigui ananoikisrelatedlncrnasignatureisausefultoolforpredictingtheprognosisofpatientswithlungadenocarcinoma AT zhuchangtai ananoikisrelatedlncrnasignatureisausefultoolforpredictingtheprognosisofpatientswithlungadenocarcinoma AT jiangxin anoikisrelatedlncrnasignatureisausefultoolforpredictingtheprognosisofpatientswithlungadenocarcinoma AT gaoyulu anoikisrelatedlncrnasignatureisausefultoolforpredictingtheprognosisofpatientswithlungadenocarcinoma AT lijiayan anoikisrelatedlncrnasignatureisausefultoolforpredictingtheprognosisofpatientswithlungadenocarcinoma AT tongyingying anoikisrelatedlncrnasignatureisausefultoolforpredictingtheprognosisofpatientswithlungadenocarcinoma AT mengzhaoyang anoikisrelatedlncrnasignatureisausefultoolforpredictingtheprognosisofpatientswithlungadenocarcinoma AT yangshigui anoikisrelatedlncrnasignatureisausefultoolforpredictingtheprognosisofpatientswithlungadenocarcinoma AT zhuchangtai anoikisrelatedlncrnasignatureisausefultoolforpredictingtheprognosisofpatientswithlungadenocarcinoma |