Research Paper Volume 16, Issue 2 pp 1276—1297
Molecular subgroup establishment and signature creation of lncRNAs associated with acetylation in lung adenocarcinoma
- 1 Department of Thoracic Surgery, Tangdu Hospital of Air Force Military Medical University, Xi’an 71003, China
- 2 Department of Ophthalmology, Tangdu Hospital of Air Force Military Medical University, Xi’an 71003, China
Received: September 8, 2023 Accepted: November 13, 2023 Published: January 17, 2024
https://doi.org/10.18632/aging.205407How to Cite
Copyright: © 2024 Chen et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Abstract
Background: The significance of long non-coding RNAs (lncRNAs) as pivotal mediators of histone acetylation and their influential role in predicting the prognosis of lung adenocarcinoma (LUAD) has been increasingly recognized. However, there remains uncertainty regarding the potential utility of acetylation-related lncRNAs (ARLs) in prognosticating the overall survival (OS) of LUAD specimens.
Methods: The RNA-Seq and clinical information were downloaded from The Cancer Genome Atlas (TCGA). Through the differential analysis, weighted correlation network analysis (WGCNA), Pearson correlation test and univariate Cox regression, we found out the prognosis associated ARLs and divided LUAD specimens into two molecular subclasses. The ARLs were employed to construct a unique signature through the implementation of the Least Absolute Shrinkage and Selection Operator (LASSO) algorithm. Subsequently, the predictive performance was evaluated using ROC analysis and Kaplan-Meier survival curve analysis. Finally, ARL expression in LUAD was confirmed by quantitative real-time PCR (qRT-PCR).
Results: We triumphantly built a ARLs prognostic model with excellent predictive accuracy for LUAD. Univariate and multivariate Cox analysis illustrated that risk model served as an independent predictor for influencing the overall survival OS of LUAD. Furthermore, a nomogram exhibited strong prognostic validity. Additionally, variations were observed among subgroups in the field of immunity, biological functions, drug sensitivity and gene mutations within the field.
Conclusions: Nine ARLs were identified as promising indicators of personalized prognosis and drug selection for people suffering with LUAD.
Abbreviations
LUAD: Lung adenocarcinoma; ARLs: Acetylation-related lncRNAs; OS: Overall survival; TCGA: The Cancer Genome Atlas; WGCNA: Weighted correlation network analysis; LASSO: Least absolute shrinkage and selection operator; lncRNAs: Long non-coding RNAs; qRT-PCR: Quantitative real-time PCR; HAMPs: Histone acetylation modulator proteins; SNVs: Simple nucleotide variations; CNV: Copy number variation; DElncRNAs: Differentially expressed lncRNAs; TMB: Tumor mutation burden; TIDE: Tumor Immune Dysfunction and Exclusion; TIICs: Tumor-infiltrating immune cells; GDSC: The Genomics of Drug Sensitivity in Cancer.