Abstract
Objective To construct a predictive signature based on autophagy-associated lncRNAs for predicting prognosis in lung adenocarcinoma (LUAD). Materials and Methods. Differentially expressed autophagy genes (DEAGs) and differentially expressed lncRNAs (DElncRNAs) were screened between normal and LUAD samples at thresholds of ∣log2Fold Change∣ > 1 and P value < 0.05. Univariate Cox regression analysis was conducted to identify overall survival- (OS-) associated DElncRNAs. The total cohort was randomly divided into a training group (n = 229) and a validation group (n = 229) and a validation group (Results A total of 30 DEAGs and 2997 DElncRNAs were identified between 497 LUAD tissues and 54 normal tissues; however, only 1183 DElncRNAs were related to the 30 DEAGs. A signature consisting of 13 DElncRNAs was built to predict OS in lung adenocarcinoma, and the survival analysis indicated a significant OS advantage of the low-risk group over the high-risk group in the training group, with a 5-year OS AUC of 0.854. In the validation group, survival analysis also indicated a significantly favorable OS for the low-risk group over the high-risk group, with a 5-year OS AUC of 0.737. Univariate and multivariate Cox regression analyses indicated that only positive surgical margin (vs negative surgical margin) and high-risk group (vs low-risk group) based on the predictive signature were independent risk factors predictive of overall mortality in LUAD. Conclusions This study investigated the association between autophagy-associated lncRNAs and prognosis in LUAD and built a robust predictive signature of 13 lncRNAs to predict OS.
Highlights
Lung cancer remains a significant public health problem threatening life, with 142,670 estimated deaths in the United States in 2019 and over 1.6 million deaths worldwide annually [1, 2]
Lung cancer generally consists of small cell lung cancer (SCLC) and non-small-cell lung cancer (NSCLC), with lung adenocarcinoma (LUAD) accounting for almost 50% of NSCLC cases [3,4,5]
The differentially expressed autophagy genes (DEAGs) and differentially expressed Long noncoding RNAs (lncRNAs) (DElncRNAs) were screened between LUAD and normal tissues by the “limma” package in R, with thresholds set as ∣ log2Fold Change ðFCÞ∣ > 1 and P value < 0.05
Summary
Lung cancer remains a significant public health problem threatening life, with 142,670 estimated deaths in the United States in 2019 and over 1.6 million deaths worldwide annually [1, 2]. Metastases of LUAD to the nervous system, bone, liver, adrenal gland and even urethra tend to indicate poor therapeutic outcomes, and only some selected cases may benefit from systematic therapy [6,7,8]. The TNM staging system provides a relatively reliable predictive model for prognosis and remains the most frequently applied predictor of survival [9]. A comprehensive investigation of the underlying molecular mechanisms and cellular pathways may be effective potential diagnostic tools and therapeutic targets for LUAD. Wholeexome sequencing and immune profiling analyses of LUAD indicated that molecular and immune phenotypes were associated with survival and response to adjuvant therapy in the clinical outcomes and personalized immune-based therapy of LUAD [10]
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