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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.
Afiliación
  • Jiang X; College of Fisheries and Life Science, Shanghai Ocean University, Shanghai, 201306, China.
  • Gao YL; Department of Transfusion Medicine, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200233, China.
  • Li JY; Department of Laboratory Medicine, Kunshan Affiliated Hospital of Nanjing University of Chinese Medicine, Kunshan, 215300, China.
  • Tong YY; College of Fisheries and Life Science, Shanghai Ocean University, Shanghai, 201306, China.
  • Meng ZY; Department of Transfusion Medicine, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200233, China.
  • Yang SG; College of Fisheries and Life Science, Shanghai Ocean University, Shanghai, 201306, China.
  • Zhu CT; Department of Pharmacy, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200233, China.
Heliyon ; 9(11): e22200, 2023 Nov.
Article en En | MEDLINE | ID: mdl-38053861
ABSTRACT

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.
Palabras clave

Texto completo: 1 Base de datos: MEDLINE Idioma: En Revista: Heliyon Año: 2023 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Base de datos: MEDLINE Idioma: En Revista: Heliyon Año: 2023 Tipo del documento: Article País de afiliación: China