A Five Autophagy-Related Long Non-Coding RNA Prognostic Model for Patients with Lung Adenocarcinoma

Abstract

Purpose: Lung adenocarcinoma is the most common pathological type among non-small cell lung cancer. Although huge progress has been made in terms of early diagnosis and precision treatment in recent years, the overall 5-year survival rate of a patient remains low. In our study, we try to construct an autophagy-related lncRNA prognostic signature that may guide clinical practice. Methods: The mRNA and lncRNA expression matrix of lung adenocarcinoma patients were retrieved from the TCGA database. Next, we constructed a co-expression network of lncRNAs and autophagy-related genes. Lasso regression and multivariate Cox regression were then applied to establish a prognostic risk model. Subsequently, a risk score was generated to differentiate the high and low risk groups and a ROC curve and nomogram to visualize the predictive ability of the current signature. Finally, gene ontology and pathway enrichment analysis were executed via GSEA. Results: A total of 1,703 autophagy-related lncRNAs were screened and five autophagyrelated lncRNAs (LINC01137, AL691432.2, LINC01116, AL606489.1, and HLA-DQB1-AS1) were finally included in our signature. Judging from univariate (HR=1.075, 95% CI=1.046-1.104) and multivariate (HR=1.088, 95% CI=1.057−1.120) Cox regression analysis, the risk score is an independent factor for LUAD patients. Further, the AUC value based on the risk score for 1-year, 3-years, and 5-years, was 0.735, 0.672, and 0.662, respectively, indicating a reliable model. Drug sensitivity analysis revealed low risk patients were more sensitive to Gemcitabine and Gefitinib, while high risk patients had a better response to Paclitaxel and Erlotinib. Moreover, the lncRNAs included in our signature were primarily enriched in the autophagy process, metabolism, p53 pathway, and JAK/STAT pathway. Finally, a multi-omics analysis of correlated genes showed CFLAR overexpressed in the tumor sample, while GAPDH and MLST8 had a slightly higher expression in the normal sample. Conclusion: Overall, our study indicated that the prognostic model we generated had certain predictability for LUAD patients' prognosis and the related genes might be potential biomarkers and therapeutic targets.

An Efficient Five-lncRNA Signature for Lung Adenocarcinoma Prognosis and Its Overall Survival Prediction

“…However, in colorectal cancer [42] , SATB2-AS1 has the effect of inhibiting tumor cell metastasis. Similar to our result, AC026355.1 was reported to be an immune-related gene with tumor suppressor effects by Li et al [30] In past studies, AL606489.1 has been reported to be associated with autophagy [43] , ferroptosis [44] , and pyroptosis [32] processes in LUAD tumor cells. LINC 01843 was rst shown to be associated with LUAD progression.…”

Transcriptome analysis of adipocytokines and their-related LncRNAs in lung adenocarcinoma revealing the association with prognosis, immune infiltration, and metabolic characteristics

“…FAM30A is involved in an immune-related prognostic signature for LUAD [ 37 ]. LINC01137 has been reported to be included in an autophagy-related prognostic signature and a redox-related prognostic signature of LUAD [ 36 , 38 ].…”

Construction of an algorithm based on oncosis‐related LncRNAs comprising the molecular subtypes and a risk assessment model in lung adenocarcinoma

“… 31 Pan et al 32 have also proved that LINC00324 promoted the proliferation and metastasis of LUAD tissues and cells by the miR‐615‐5p/AKT1 pathway. However, in the remaining orlncRNAs of 11 orlncRNAs (e.g., AC010980.2, 33 , 34 , 35 , 36 AL365203.2, 37 , 38 , 39 AL606489.1, 34 , 40 AC004687.1, 41 , 42 , 43 HLA‐DQB1‐AS1, 44 , 45 , 46 , 47 and AL590226.1, 48 although there are few experiments to explore their relationship with the occurrence and development of malignant tumors, plenty of prognostic signatures have included them to predict the OS of patients with various malignant tumors.…”